SBA系统的综合集成研讨厅研究与应用
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摘要
“基于仿真的采办”(Simulation Based Acquisition,SBA)是近年来逐步得到美国国防部和国防工业界认可的一种新的采办理念,是现代武器系统采办虚拟化、集成化发展的必然。而综合集成研讨厅是推动传统采办向基于仿真的采办发展的一项引擎技术。本文以国防“十·五”重点预研项目为背景,着重研究了面向国内武器装备采办的SBA总体框架及其原型系统,并对原型系统中的一个子系统——综合集成研讨厅进行了深入的研究。
本文首先回顾和分析了美国SBA专门小组提出的SBA体系结构,在借鉴的基础上,研究了国内传统的串行武器采办流程,针对性的建立了基于并行工程原理的SBA工程的系统结构,描述了SBA过程的特点,然后根据这些特点和要求建立了适合国内武器装备采办的SBA总体框架和原型系统,对原型系统的组成及其功能进行了详细阐述,并分析了系统实现的关键问题与难点,为其它SBA相关研究奠定了基础。
为求解现有的常规决策方法与系统工程方法难以处理的复杂决策问题,如采办过程中的武器装备论证问题,提出了一种综合集成型决策支持系统(也就是面向复杂问题求解的综合集成研讨厅)。分析了当前各种决策支持系统的特点和存在的问题,运用并根据复杂决策问题求解的综合集成过程明确了系统的需求,建立了满足需要的基于浏览器/服务器模式的开放的系统体系结构,讨论了其组成和功能,并运用面向对象的建模方法对系统进行了总体静态设计,介绍了系统实现的关键技术——模型、仿真、信息、意见以及知识的综合集成。
针对模型综合集成技术,分别运用Agent和Web服务两种技术研究了分布式模型管理与动态、自动组合方法。一种方法将模型设计为Agent,建立了基于管理Agent和模型Agent的星型结构的多Agent模型系统,设计了两种Agent的结构,分析了它们的功能和行为,利用逆向推理技术实现模型Agent的动态、自动组合,从而实现了以下功能:模型远程调用与分布管理;模型具有可重用性;用户不需要知道模型是如何实现的;不需要手工组合多个模型来求解复杂的问题等。另一种方法将模型视为Web服务,利用OWL-S语言描述Web服务,利用语义Web技术实现模型的查找与匹配,结合语义Web技术和充分考虑用户可提供知识的改进的逆向推理技术实现模型的自动组合,同样实现了多Agent模型系统可以实现的功能,且更具柔性。实现分布式模型管理与模型自动组合功能,使得研讨厅的机器体系可充分发挥其“定量”综合集成的优势,也使得专家可以更好地发挥其经验智慧来解决
Simulation Based Acquisition (SBA) is a kind of new idea of acquisition progressively adopted by Department of Defense (DOD) and Industry in recent years, which represents the direction of weapon system acquisition modes. While, Hall for Workshop of Metasynthetic Engineering(HWME) is an enable technology to impel the development of acquisition from traditional mode to SBA mode. Thus, take the project supported by the National Defence pre-research Foundation as background, this dissertation mainly develops an inland SBA framework and the corresponding prototype system, and explores a sub-system of prototype system, which is HWME. As follows in detail:In this paper, by analyzing the SBA architecture proposed by the Joint SBA Task Force and using it as a guide, the inland traditional sequential acquisition process is studied, the shortfalls within which are identified, and then the SBA Engineering architecture is established based on Concurrent Engineering theory. SBA process is a spiral or iterative process rather than a waterfall process that leads to the development and fielding of a new weapon system. Following, according to the characteristics and requirements of SBA Engineering, a framework of SBA is developed, which describes the support platforms/tools and application systems etc. the SBA system should include; and an architecture of prototype SBA system which can direct implementation is put forward, which including collaborative platform of management and control, Hall for Workshop of Metasynthetic Engineering, collaborative simulation platform, collaborative PDM, ERP, Computer-Aided Logistic Support and distributed resource database system etc. Next, the key technologies piloting the implement of the prototype system are analyzed.To deal with complicated decision-making problems solved difficultly in rule decision-making methods and system engineering methods, such as problems of demonstration of weapon and equipment, the Meta-synthetic Decision Support System (MSDSS, i.e. Hall for Workshop of Metasynthetic Engineering for complicated decision-making problems) is proposed. By analyzing characteristics and existing problems in current DSS, the requirements of MSDSS are put forward according to the Meta-synthetic process for complicated decision-making. Furthermore, the open
architecture of MSDSS catering to requirements based on Browser/Server is established; the components and functions of the system are discussed. And the static design of the system is conducted using method of Object-oriented modeling. Also, the key technologies such as model synthesizing, simulation synthesizing, information synthesizing, opinion synthesizing and knowledge synthesizing are introduced.To model synthesizing, two approaches to distributed model management and automatic composition are developed. One method designs the model as agent, so, a multi-agent model system with star structure is built, which consists of one management agent and amount of model agents. Then the structures of two kinds of agents are designed, and their functions and actions are analyzed. Furthermore, a backward chaining algorithm is addressed to compose the existing model agents in a dynamic and automatic way, which realizes the following functions: model can be managed in a distributed way and calling remotely, model can be reused, customers needn't know how models are implemented, and composing several models to solve complicated problems manually is unnecessary etc. Another method takes models as Web services, describes Web service with OWL-S, and using semantic web technology to finding and matching models, and combining semantic web technology and an improved backward chaining algorithm to compose the models semantically and automatically, which also implements the functions that multi-agent model system does, while, it is more flexible. Realizing the function of distributed model management and automatic composition makes the machine system of HWME may employ its quantitative meta-synthesis to maximum advantage, and also makes the experts may employ their experience and wisdom to a more perfect advantage to solve complicated problems, with no necessary to master too much knowledge about model.During the course of discussing, a problem should be considered is that how to aggregate experts' distributed thinking to reach consensus. Thus, a new consensus method on basis of linguistic assessment information is proposed, which considers not only using nature language to evaluate is more approaching to fact and more favored by experts, but also high efficiency feature of computer in dealing with numeric problems. Within the method, a new algorithm for aggregation of several triangle fuzzy numbers is proposed, according to it, the opinion which has high consensus degree with other opinions will be more reflected in group opinion, while the opinion which has little consensus degree with other opinions will occupy a subordinate position in group opinion. Also, the algorithm may integrate the weights of experts, which will make the
本文首先回顾和分析了美国SBA专门小组提出的SBA体系结构,在借鉴的基础上,研究了国内传统的串行武器采办流程,针对性的建立了基于并行工程原理的SBA工程的系统结构,描述了SBA过程的特点,然后根据这些特点和要求建立了适合国内武器装备采办的SBA总体框架和原型系统,对原型系统的组成及其功能进行了详细阐述,并分析了系统实现的关键问题与难点,为其它SBA相关研究奠定了基础。
为求解现有的常规决策方法与系统工程方法难以处理的复杂决策问题,如采办过程中的武器装备论证问题,提出了一种综合集成型决策支持系统(也就是面向复杂问题求解的综合集成研讨厅)。分析了当前各种决策支持系统的特点和存在的问题,运用并根据复杂决策问题求解的综合集成过程明确了系统的需求,建立了满足需要的基于浏览器/服务器模式的开放的系统体系结构,讨论了其组成和功能,并运用面向对象的建模方法对系统进行了总体静态设计,介绍了系统实现的关键技术——模型、仿真、信息、意见以及知识的综合集成。
针对模型综合集成技术,分别运用Agent和Web服务两种技术研究了分布式模型管理与动态、自动组合方法。一种方法将模型设计为Agent,建立了基于管理Agent和模型Agent的星型结构的多Agent模型系统,设计了两种Agent的结构,分析了它们的功能和行为,利用逆向推理技术实现模型Agent的动态、自动组合,从而实现了以下功能:模型远程调用与分布管理;模型具有可重用性;用户不需要知道模型是如何实现的;不需要手工组合多个模型来求解复杂的问题等。另一种方法将模型视为Web服务,利用OWL-S语言描述Web服务,利用语义Web技术实现模型的查找与匹配,结合语义Web技术和充分考虑用户可提供知识的改进的逆向推理技术实现模型的自动组合,同样实现了多Agent模型系统可以实现的功能,且更具柔性。实现分布式模型管理与模型自动组合功能,使得研讨厅的机器体系可充分发挥其“定量”综合集成的优势,也使得专家可以更好地发挥其经验智慧来解决
Simulation Based Acquisition (SBA) is a kind of new idea of acquisition progressively adopted by Department of Defense (DOD) and Industry in recent years, which represents the direction of weapon system acquisition modes. While, Hall for Workshop of Metasynthetic Engineering(HWME) is an enable technology to impel the development of acquisition from traditional mode to SBA mode. Thus, take the project supported by the National Defence pre-research Foundation as background, this dissertation mainly develops an inland SBA framework and the corresponding prototype system, and explores a sub-system of prototype system, which is HWME. As follows in detail:In this paper, by analyzing the SBA architecture proposed by the Joint SBA Task Force and using it as a guide, the inland traditional sequential acquisition process is studied, the shortfalls within which are identified, and then the SBA Engineering architecture is established based on Concurrent Engineering theory. SBA process is a spiral or iterative process rather than a waterfall process that leads to the development and fielding of a new weapon system. Following, according to the characteristics and requirements of SBA Engineering, a framework of SBA is developed, which describes the support platforms/tools and application systems etc. the SBA system should include; and an architecture of prototype SBA system which can direct implementation is put forward, which including collaborative platform of management and control, Hall for Workshop of Metasynthetic Engineering, collaborative simulation platform, collaborative PDM, ERP, Computer-Aided Logistic Support and distributed resource database system etc. Next, the key technologies piloting the implement of the prototype system are analyzed.To deal with complicated decision-making problems solved difficultly in rule decision-making methods and system engineering methods, such as problems of demonstration of weapon and equipment, the Meta-synthetic Decision Support System (MSDSS, i.e. Hall for Workshop of Metasynthetic Engineering for complicated decision-making problems) is proposed. By analyzing characteristics and existing problems in current DSS, the requirements of MSDSS are put forward according to the Meta-synthetic process for complicated decision-making. Furthermore, the open
architecture of MSDSS catering to requirements based on Browser/Server is established; the components and functions of the system are discussed. And the static design of the system is conducted using method of Object-oriented modeling. Also, the key technologies such as model synthesizing, simulation synthesizing, information synthesizing, opinion synthesizing and knowledge synthesizing are introduced.To model synthesizing, two approaches to distributed model management and automatic composition are developed. One method designs the model as agent, so, a multi-agent model system with star structure is built, which consists of one management agent and amount of model agents. Then the structures of two kinds of agents are designed, and their functions and actions are analyzed. Furthermore, a backward chaining algorithm is addressed to compose the existing model agents in a dynamic and automatic way, which realizes the following functions: model can be managed in a distributed way and calling remotely, model can be reused, customers needn't know how models are implemented, and composing several models to solve complicated problems manually is unnecessary etc. Another method takes models as Web services, describes Web service with OWL-S, and using semantic web technology to finding and matching models, and combining semantic web technology and an improved backward chaining algorithm to compose the models semantically and automatically, which also implements the functions that multi-agent model system does, while, it is more flexible. Realizing the function of distributed model management and automatic composition makes the machine system of HWME may employ its quantitative meta-synthesis to maximum advantage, and also makes the experts may employ their experience and wisdom to a more perfect advantage to solve complicated problems, with no necessary to master too much knowledge about model.During the course of discussing, a problem should be considered is that how to aggregate experts' distributed thinking to reach consensus. Thus, a new consensus method on basis of linguistic assessment information is proposed, which considers not only using nature language to evaluate is more approaching to fact and more favored by experts, but also high efficiency feature of computer in dealing with numeric problems. Within the method, a new algorithm for aggregation of several triangle fuzzy numbers is proposed, according to it, the opinion which has high consensus degree with other opinions will be more reflected in group opinion, while the opinion which has little consensus degree with other opinions will occupy a subordinate position in group opinion. Also, the algorithm may integrate the weights of experts, which will make the
引文
[1] DoD EXCIMS Industry Steering Group. SBA Functional Description-Version 1.1. http://www.msosa.dmso.mil/sba_documents/, 1999, 2.24.
[2] Department of the Navy Acquisition Reform Office. Simulation Based Acquisition (SBA) status and international implications. http://www.msiac.dmso.mil/sba_documents/SBA%20status%20&%20internat'1%20imp.pdf, 2000, 9.
[3] Parker T. Final Report of the Acquisition Task Force on Modeling and Simulation. DDR&E Acquisition Task Force, Jun. 1994.
[4] Portmann H H. Study on the Application of Modeling and Simulation to the Acquisition of Major Weapon Systems. American Defense Preparedness Association (ADPA), Sep. 1996.
[5] Naval Research Advisory Committee. Naval Research Advisory Committee Report on Modeling and Simulation, NRAC 94-3, Nov. 1994.
[6] James E. Coolahan. A Simulation Based Acquisition Collaborative Environment for Strike Warfare, 6th Annual JAWS S3 Symposium and Exhibition, June 2000.
[7] Col Phil Faye. Simulation Based Acquisition Re-Engineering Acquisition for 2005 and Beyond, AFMC SBA, Dec. 2000.
[8] BDM Federal, Inc. Collaborative Virtual Prototyping Sector Study. North American Technology and Industrial Base Organization, May 1996.
[9] Patenaude A. Study on the Effectiveness of Modeling and Simulation in the Weapon System Acquisition Process. Oct. 1996.
[10] Forst R. Simulation Based Acquisition an Ongoing Look. 98F-SIW. 1998.
[11] DoD SBA Task Force. A Roadmap for Simulation Based Acquisition. http://www.msosa.dmso.mil/sba/documents.asp, 1998, 12.4.
[12] David S. The Role of System Modelling and Simulation in Royal Australian Navy Capability Management. DSTO-GD-0244. http://www.dsto.defence.gov.au/corporate/reports/, July 2000.
[13] LCdr J. United Kingdom National Experience in Simulation, Modelling and Synthetic Environments. NATO Modelling and Simulation Conference. Norfolk, Virginia, USA. October 1999.
[14] Vice-Chief of the Defence Staff Group. Modelling and Simulation: Enabling the Creation of Affordable, Effective 2020 Canadian Forces, http://www.vcds.dnd.ca/intro_e.asp, Apr. 2000.
[15] NATO Modelling and Simulation Master Plan. North Atlantic Treaty Organisation Document AC/323 (SGMS)D/2.www.drdc-rddc.dnd.ca/seco/documents, 7 August 1998.
[16] 李伯虎,王行仁,黄柯棣等.综合仿真系统研究.系统仿真学报,2000,12(5):429-434.
[17] 熊光楞,李伯虎等.虚拟样机技术.系统仿真学报,2001,13(1):114-117.
[18] 柴旭东,李伯虎,熊光楞等.复杂产品协同仿真平台的研究与实现.计算机集成制造系统—CIMS,2002,8(7):580-584.
[19] 郭斌,熊光楞,陈晓波.支持复杂产品设计的协同仿真平台研究.机械与电子,2002,4:26-29.
[20] 王江云,王行仁,贾荣珍.协同仿真环境体系结构.系统仿真学报,2001,13(6):687-689.
[21] 魏华梁,刘藻珍,李钟武.二十一世纪武器系统仿真新动向-基于仿真的采办与管理.计算机仿真,2000,17(4):24-28.
[22] 李伯虎,柴旭东,毛媛.现代仿真技术发展中的两个热点——ADS,SBA.系统仿真学报,2001,13(1):101-105.
[23] 黄柯棣等.略论军用仿真技术面临的需求与发展的方向.系统仿真学报.2001(1):6-10.
[24] 段红,黄柯棣.基于仿真的采办体系结构.系统仿真学报,2001,13(2):247-250.
[25] 段红,黄柯棣,李革.基于仿真的采办协同环境研究.系统仿真学报,2002,14(2):149-151.
[26] 王江云,林新,王行仁.基于HLA的SBA协同环境研究.计算机仿真,2001,18(5):7-9.
[27] Jacques S. Gansler. Life-Cycle Modeling and Simulation A Key Element in Acquisition Reform. http://www.acq.osd.mil/acqweb/usd/, 1998.
[28] James W. Hollenbach. Department of the Navy (DON) Corporate Approach to Simulation Based Acquisition (SBA). http://www.acq-ref.navy.mil/, 2000.
[29] Dahmann J. SBA Yesterday & Today: Current View of SBA in Advanced Systems Engineering and System-of-Systems Environment. http://www.dtic.mil/ndia/2002sba/dahmann.pdf, 2002.
[30] James W. Hollenbach. The Joint Strike Force (JSF) Distributed Product Description (DPD). http://www.sisostds.org/siw/, 2000.
[31] James W. Hollenbach. JSF Modeling Information Management. http://www.sisostds.org/siw/, 2000.
[32] Richard A. Reading, Pobat M. Common Threat Representation in Simulation and Testing of Ship Self Defense. http://www.sisostds.org/siw/, 2000.
[33] Frost R. Simulation Based Acquisition, The Initiative. www.msiac.dmso.mil/sba_documents/, 2001.
[34] Smith R. Simulation Based Acquisition. http://www.modelbenders.com/sba/, 1998.
[35] 戴汝为.21世纪组织管理途径的探讨.管理科学学报,1999,1(3):1-6.
[36] 成思危.复杂科学与系统工程.工管理科学学报,1999,2(2):1-7.
[37] 金吾伦,郭元林.复杂性科学及其演变.复杂系统与复杂性科学,2004,1(1):1-5.
[38] 戴汝为.复杂巨系统科学——一门21世纪的科学.自然杂志,1997,7(2):187-192.
[39] 钱学森,于景元,戴汝为.一个科学的新领域——开放的复杂巨系统及其方法论.自然杂志,1990,13(1):3-10.
[40] 钱学森.再谈开放的复杂巨系统.模式识别与人工智能,1991,4(1):5-8.
[41] 戴汝为,王珏,田捷.智能系统的综合集成.杭州:浙江科学技术出版社,1995.
[42] 戴汝为 操龙兵.综合集成研讨厅的研制.管理科学学报,2002,5(3):10-16.
[43] 钱学森.论系统工程.长沙:湖南科学技术出版社,1982.
[44] 钱学森.社会主义建设的总体设计部[A].创建系统学[M].太原:山西科学技术出版社,2001.134.
[45] 于景元,周晓纪.综合集成方法与总体设计部.复杂系统与复杂性科学,2004,1(1):20-26.
[46] 于景元,钱学森.关于开放的复杂巨系统的研究.系统工程理论与实践,1992,12(5):8-12.
[47] 戴汝为.从定性到定量的综合集成技术.模式识别与人工智能,1993,6(2):60-65.
[48] 王寿云等.开放的复杂巨系统.杭州:浙江科学技术出版社,1995.
[49] 艾克武,胡晓惠.综合集成的内容与方法——复杂巨系统问题研究.系统工程与电子技术,1998,7:17-23.
[50] 胡晓峰.系统集成与系统综合集成.测控技术,1999,18(9):11-13.
[51] 戴汝为.系统科学与思维科学交叉发展的硕果——大成智慧工程.系统工程理论与实践,2002,5:8-11.
[52] 于景元,刘毅.复杂性研究与系统科学.科学学研究,2002,20(5):449-453.
[53] 于景元,涂元季.从定性到定量综合集成方法——案例研究.系统工程理论与实践,2002,5:1-7.
[54] 于景元,周晓纪.从定性到定量综合集成方法的实现和应用.系统工程理论与实践,2002,10:26-32.
[55] 苗东升.综合集成法的认识论基础.系统辨证学学报,2003,11(1):37-42.
[56] 王丹力,戴汝为.综合集成研讨厅体系中专家群体行为的规范.管工管理科学学报,2001,4(2):1-6.
[57] 崔霞,戴汝为,李耀东.群体智慧在综合集成研讨厅体系中的涌现.系统仿真学报,2003,15(1):146-153.
[58] 崔霞,李耀东,戴汝为.HWME中基于学习型组织的专家有效互动对话模型.管理科学学报,2004,7(2):80-87.
[59] 操龙兵,戴汝为.基于Internet的综合集成研讨厅系统体系结构.计算机科学,2002,29(6):6-66.
[60] 操龙兵,戴汝为.综合集成研讨厅的软件体系结构.软件学报,2002,13(8):1430-1435.
[61] 鲁东明,张晓宇,潘云鹤.基于知识碰撞模型的虚拟研讨厅系统.计算机研究与发展,2002,39(12):1720-1727.
[62] 胡晓峰,司光亚.战略决策综合集成研讨环境SDE98的体系结构.小型微型计算机系统,1999,20(2)88-91.
[63] 胡晓峰,司光亚,吴琳等.SDS2000-一个定性定量结合的战略决策综合集成研讨与模拟环境.系统仿真学报,2000,12(6):595-599.
[64] 司光亚.战略决策综合集成研讨与模拟环境与实现[博士学位论文].长沙:国防科技大学,2000.
[65] 王丹力,戴汝为.群体一致性及其在研讨厅中的应用.系统工程与电子技术,2001,23(7):33-37.
[66] 顾基发.意见综合—怎样达成共识.系统工程学报,2001,16(5):340-348.
[67] 孙景乐,张朋柱.一种互补的研讨框架的设计与实现.系统工程学报,2001,16(5):360-365.
[68] 程少川,张朋柱,卢明德.群体过程信息的树状结构及其定性收敛的研究.系统工程学报,2001,16(5):371-375.
[69] 彭本红,孙绍荣,张文健.研讨厅中专家意见的可靠性研究.系统工程理论方法应用,2004,13(4):343-346.
[70] The Consensus Building Institute, http://www.cbi-web.org/home.htm, 2002.
[71] 唐锡晋.模型集成.系统工程学报,2001,16(5):322-329.
[72] 胡代平,王浣尘.基于多Agent的模型系统研究.系统工程理论方法应用,2001,10(2):89-92.
[73] Chari K. Model composition in a distributed environment. Decision Support Systems, 2003, 35: 399-413.
[74] 毛海军,唐焕文,李飞.宏观经济智能预测决策支持系统模型系统的Agent实现研究.计算机工程与应用,2003,15:77-79.
[75] 谢勇,王红卫.基于逆向推理策略的模型集成.计算机集成制造系统—CIMS,2002,8(9):690-694.
[76] 谢勇,王红卫.模型集成及其优化策略.计算机集成制造系统—CIMS,2005,11(1):58-62.
[77] 司光亚,胡晓峰.战略决策模拟环境中XOD综合集成机制的研究与实现.小型微型计算机系统,2002,23(2):242-245.
[78] 杨镜宇,吴琳,司光亚等.战争系统中面向按需服务的仿真资源综合集成问题研究.系统仿真学报,2003,15(12):1683-1686.
[79] 王黎明,毛汉英.区域可持续发展综合集成研讨厅体系研究.地理研究,1998,17(4): 408-414.
[80] 常显奇等.空间军事系统综合集成研讨厅内容体系的研究与建设.系统工程理论与实践,2001,6(5):86-90.
[81] 胡代平,王浣尘.基于Agent的宏观经济决策支持系统.系统工程理论与实践,2001,1:33-37.
[82] Cao L B, Dai R w. Autonomous intelligent agents for metasynthetic engineering: a macroeconomic decision support system. First International Congress on Autonomous Intelligent Systems(1CAIS2002), Geelong, Australia, 2002.
[83] 张景涛,王丹力,王宏安等.敏捷供应链管理的综合集成研讨厅.系统工程学报,2003,18(6):515-520.
[84] 吴晓伟,徐福缘,吴伟昶.基于“综合集成研讨厅”的企业竞争情报系统研究.情报学报,2004,23(6):746-754.
[85] Dolk D R. Model Integration and a Theory of Models. Decision Support Systems, 1993, 9:51-63.
[86] Lenard M L. An Object-Oriented Approach to Model Management. Decision Support Systems, 1993, 9 (1): 67-73.
[87] Ling T P, Konsynski B. Modeling by Analogy: Use of Analogical Reasoning in Model Management Systems. Decision Support Systems, 1993, 9:113-125.
[88] Liang T P. Analogical Reasoning and Case-based Learning in Model Management. Decision Support Systems, 1993, 10: 137-160.
[89] Muhanna W A. An Object-Oriented Framework for Model Management and DSS Development. Decision Support Systems, 1993, 9: 217-229.
[90] Basu A, Blanning R W. Model Integration Using Metagraphs. Information Systems Research, 1994, 5(3): 195-218.
[91] Muhanna W A, Pick R A. Meta-Modeling Concepts and Tools for Model Management: A Systems Approach. Management Science, 1994, 40(9): 1093-1123.
[92] 周宽久,黄梯云.面向对象的模型表示与模型复合.哈尔滨工业大学学报,1997,29(4):18-20.
[93] Andrea E. Rizzoli J. Davis R, et al. Model and Data Integration and Re-use in Environmental Decision Support Systems. Decision Support Systems, 1998, 24(2):127-144.
[94] 王林,高国安.面向对象的IDSS模型库系统的构造.电脑与信息技术,2000,(1):1-5.
[95] 杜江,孙玉芳.基于面向对象模型库的DSS可重用体系结构研究.系统工程理论与实践,2000,(1):1-6.
[96] 黄跃进,反伟胜,朱云龙.空间决策支持系统模型库系统研究.信息与控制,2000,29(3):219-224.
[97] 赵新昱,陈文伟,张维明等.基于构件的决策支持系统中模型组织集成框架IFMO.国防科技大学学报,2001,23(2):61-65.
[98] Henderson S. The Design and Development of a Flexible Component-based Decision Support System Generator. A research essay presented to the University of Auckland in partial fulfilment of the requirements for the Degree of BCom(Hons) in Management Science and Information Systems. December 2001.
[99] 马金平.基于ActiveX组件技术的模型库系统的开发研究.计算机应用,2001,20(5):33-35.
[100] 魏继才,董文洪,胡晓峰等.智能决策系统中模型服务器的设计与实现.计算机仿真,2003,20(1):22-24.
[101] 魏继才,胡晓峰,范波涛等.综合集成决策模拟系统中模型的设计与实现.计算机仿真,2003,20(1):25-28.
[102] 彭英武,严建钢,司光亚等.分布式环境中模型服务实现中的若干关键技术.计算机应用.2003,23(5):58-61.
[103] 林杰,张丽峰,薛行.基于UDDI的分布模型管理.计算机集成制造系统—CIMS,2004,10(3):276-280.
[104] 林杰,雷星晖,王效俐.基于Web服务的分布模型管理系统的研究.计算机应用,2004,24(4):80-82.
[105] 张振兴,王翠茹,刘建峰等.基于Web服务的模型库系统的研究与实现.华北电力大学学报,2003,30(4):78-81.
[106] 黄卓,张涛,郭波.基于Web Service的分布模型管理方法研究.计算机工程与设计,2004,25(3):379-380.
[107] 周昭权,薛永生,黄震华.基于Web Service的DSS模型重用机制研究.厦门大学学报,2004,43(6):776-781.
[108] Byung Kwon O. Meta web service: building web-based open decision support system based on web services. Expert Systems with Applications, 2003, 24: 375-389.
[109] 王慧斌、徐小群.综合集成研讨厅体系及应用研究.信息与控制,2001,30(6):516-521.
[110] 张朋柱,刁石京.我国政府宏观决策任务的分类研究.系统工程学报,2001,16(5):354-359.
[111] 沈惠璋,王浣尘.基于演化模型的宏观经济系统分析方法.系统工程学报,2001,16(5):389-393.
[112] 葛新元,王大辉,袁强等.多部门经济动力学模型及其合理性分析.系统工程学报,2001, 16(5):397-401.
[113] 舒光复.综合集成系统重构及宏观经济研究中的应用.系统工程学报,2001,16(5):349-353.
[114] The Consensus Building Institute. http://www.cbuilding.org/consensus/index.html, 2005-4-10.
[115] Leher K, Wagner C. Rational consensus in science and society. Dordecht: Reidel, 1981.
[116] Schuman S, Richardson J. Decision conferencing for systems planning. Information and Management, 1991, 21:147-159.
[117] Lawrence Butler C T. Amy Rothstein. The book On Conflict and Consensus, http://www.wandreilagh.org/consensus.pdf, 2005.
[118] Consensus Technology. The art and science of collaborative decision making. http://www.consensustech.com/, 2005.4.10.
[119] Consensus-How to and Why. http://www.msu.edu/～corcora5/org/consensus.html.
[120] The Team Resource Center Servies. http://www.team-creations.com/Services/meeting.htm.
[121] Hiltz S R, Turoff M, et al. Distributed group support systems: theory development and experimentation[A]. Coordination theory and collaboration technology[M]. Erlbaum Associates, 1996.
[122] DeGroot M H. Reaching a consensus. Journal of the American Statistical Association, 1974, 69:118-212.
[123] Kacprzyk J, Nurmi H, Fedrizzi M. Consensus under fuzziness. Dordrecht: Kluwer Academic Publishers, 1997.
[124] Kacprzyk J, Fedrizzi M, Nurmi H. "Soft" degrees of consensus under fuzzy preference and fuzzy majorities[A]. Consensus under fuzziness[M]. Dordrecht: Klawer Academic Publishers, 1997, 55-82.
[125] Zadrozny S. An approach to the consensus reaching support in fuzzy environment [A]. Consensus under fuzziness [M]. Dordrecht: Klawer Academic Publishers, 1997. 83-109.
[126] Seo F. Construction of fuzzy utility function in group decision making[A]. Consensus under fuzziness[M]. Dordrecht: Klawer Academic Publishers, 1997. 211-230.
[127] Herrera F, Hrrera-Viedma E, Verdegay J L. A model of consensus in group decision making under linguistic assessments. Fuzzy Sets and Systems, 1996, 79: 73-87.
[128] Herrera F, Herrera-Viedma E, Verdegay J L. A rational consensus model in group decision making using linguistic assessments. Fuzzy Sets and Systems, 1997, 88: 31-49.
[129] 王丹力,戴汝为.群体一致性及其在研讨厅中的应用.系统工程与电子技术,2001,7:33-37.
[130] 涂承胜,鲁明羽,陆玉昌.Web挖掘研究综述.计算机工程与应用,2003,(10):90-93.
[131] Enriching Representations of Work to Support Organisational Learning, http://kmi.open.ac.uk/projects/enrich/, 2005-04-10.
[132] Mulholland P, Zdrahal Z, Domingue J A, et al. A Methodological Approach to Supporting Organizational Learning. International Journal of Human-Computer Studies, 2001, 55(3): 337-367.
[133] Mulholland P, Domingue J, Zdrahal Z, et al. Organisational Learning: An Overview of the Enrich Approach. Journal of Information Services and Use, 2000, 20(1): 9-23.
[134] The ClockWork Project, http://kmi.open.ac.uk/projects/clockwork/, 2005-4-10.
[135] Mulholland P, Zdrahal Z, Sainter P, et al. Supporting the sharing and reuse of modelling and simulation engineering knowledge. International Conference on Concurrent Enterprising (ICE2003), Espoo, Finland, 16-18 June.
[136] Zdrahal Z, Mulholland P, Valasek M, Sainter P, Koss, et al. A toolkit and methodology to support the collaborative development and reuse of engineering models. Database and Expert Systems Applications Conference (DEXA 2003), Prague, Czech Republic.
[137] Mizoguchi R, Kitamura Y, Arai E, et al. A Methodology of Collaborative Synthesis by Artificial Intelligence http://www.ei.sanken.osaka-u.ac.jp/pub/miz/miz-skfcw99.pdf.
[138] http://new-humanity.narod.ru.
[139] Sandelowski. M, Barroso J. Writing the Proposal for a Qualitative Research Methodology Project. Qualitative Health Research, 2003, 13: 781-820.
[140] Sandelowski. M, Barroso J. Reading Qualitative Studies, International Journal of Qualitative Methods, 2002, 1(1), Article 5. http://www.ualberta.ca/～ijgm/.
[141] 常鑫,殷红海.Daniel Kahneman与行为经济学.http://www.psychcn.com/psyhistory/200502/1650311539.shtml.
[142] Jams W. Hollenbach. Collabrative Achievement of Advanced Acquisition Environments, September 2001, http://www.acq-ref.navy.mil/reflib/.
[143] 李明,刘澎.武器装备发展系统论证方法与应用[M].北京:国防工业出版社,2000.
[144] Peggy D. Gravitz, Sheehan J, McLean T. Common activities in Data Interchange Format (DIF) development, http://www.sisostds.org/doclib/doclib.cfm?SISO_RID_1000944,1999, 2.3.
[145] 王鹏,李伯虎,柴旭东等.复杂产品虚拟样机协同仿真建模技术研究.系统仿真学报,2004,16(2):274-277.
[146] 张建明.基于仿真的采办若干关键理论和技术研究[博士学位论文].南京,南京理工大学,2004.11
[147] 操龙兵,戴汝为.综合集成与决策[J].计算机研究与发展,2003,40(4):531-537.
[148] Carlsson C, Turban E. DSS: directions for the next decade (Introduction of the journal Decision Support Systems). Decision Support Systems, 2002, 33(2): 105-110.
[149] 胡晓惠.研讨厅系统实现方法及技术的研究.系统工程理论与实践,2002,(6):1-10.
[150] 陈文伟.决策支持系统及其开发.北京:清华大学、广西科学技术出版社,2000.
[151] Peltonen H. Concepts and an Implementation for Product Data Management[Doctor thesis]. Helsinki: Department of Computer Science and Engineering, Helsinki University of Technology, 2000.
[152] 王博,晓龙.面向对象的建模设计技术与方法.北京:学苑出版杜,1993.
[153] Page-Jones M.UML面向对象设计基础.北京:人民邮电出版社,2001.
[154] 黄海量.产品开发网络化协同决策方法与使能技术研究[博士学位论文].西安:西安交通大学,2002.
[155] Extensible Markup Language (xml) 1.0 (second edition), http://www.w3.org/XML.
[156] Tsalgatidou A, Pilioura T. An Overview of Standards and Related Technology in Web Services. Distributed and Parallel Databases, 2002, 12 (2-3): 135.
[157] Benatallah B, Dumas M, Fauvet M C, et al. Towards Patterns of Web Services Composition. In S. Gorlatch and F. Rabhi, editors, Patterns and Skeletons for Parallel and Distributed Computing. Springer Verlag, UK, Nov. 2002.
[158] Lee K W, Huh S Y. Model-Solver Integration in Decision Support Systems: A Web Services Approach. http://mis.temple.edu/sigdss/icis03/proceedings/DSSWorkshop03-Lee.pdf, 2003.
[159] W3C Web Services Activity. http://www.w3.org/2002/ws/.
[160] Web Service Choreography Interface (WSCI) 1.0, 8 August 2002. http://www.w3.org/TR/wsci/.
[161] Business Process Execution Language for Web Services version 1.1, May 2003. http://www-128.ibm.com/developerworks/library/specification/ws-bpel/.
[162] Lee T B. Semantic Web Architecture. http://www.w3.org/2000/talks/1206-xml2k-tbl/slide10-0.html, 2001-07-20.
[163] OWL-S Coalition. OWL-S 1.1 release, http://www.daml.org/services/owl-s/1.1/.
[164] Wu D, Parsia B, Sirin E, et al. Automating DAML-S Web Services Composition Using SHOP2. www.mindswap.org/papers/ISWC03-SHOP2.pdf, 2003.
[165] Paolucci M, Kawamura T, Terry R. Payne, et al. Semantic Matching of Web Services Capabilities. In International Semantic Web Conference, Sardinia, Italy, June 9-12, 2002.
[166] Akash M, Bercovier M, Marowka A, et al. Towards Virtualization of On-Demand Web Service Composition Using an Improved Ranking Algorithm. Proceedings of the International Symposium on Web Services & Applications, ISWS'04, Las Vegas, Nevada, USA, June 21-24, 2004. http://scom.hud.ac.uk/scomzl/conference/chenhua/040528_01E/ISW2037.pdf.
[167] Dale J, Ceccaroni L. Pizza and a Movie: A Case Study in Advanced Web Services. Proceedings of the workshop AAMAS 2002-W04: Challenges in Open Agent Systems. http://www.nar.fujitsulabs.com/documents/fla-nartm02-03.pdf.
[168] 蔡铭、林兰芬、董金祥.网络化制造环境中制造服务智能匹配技术研究.计算机辅助设计与图形学学报,2004,16(8):1090-1096.
[169] 张蓉、申德荣等.基于本体的Web服务查找与合成技术研究.计算机集成制造系统—CIMS,2003,9(10):922-925.
[170] Sirin E, Hendler J, Parsia B. Semi-automatic Composition of Web Services using Semantic Descriptions. http://www.mindswap.org/papers/composition.pdf, 2003.
[171] Lin M S, Guo H O, Yin J F. Goal Description Language for Semantic Web Service Automatic Composition. Proceedings of the 2005 Symposium on Applications and the Internet (SAINT'05). http://doi.ieeecomputersociety.org/10.1109/SAINT.2005.33.
[172] Aversano L, Canfora G, Ciampi A. An algorithm for Web service discovery through their composition. Proceedings of the IEEE International Conference on Web Services (ICWS'04), June 6-9, 2004, San Diego, California, USA.
[173] Seyyed V. Hashemian, Mavaddat F. A Graph-Based Approach to Web Services Composition. Proceedings of the 2005 Symposium on Applications and the Internet (SAINT'05). http://doi.ieeecomputersociety.org/10.1109/SAINT. 2005.4
[174] Alfaro L, Henzinger T A. Interface Automata, Proceedings of the 8th European software engineering conference held jointly with 9th ACM SIGSOFT international symposium on Foundations of software engineering, ACM Press, pp. 109-120, 2001.
[175] Sirin E, Parsia B, Hendler J. Filtering and Selecting Semantic Web Services with Interactive Composition Techniques. IEEE Intelligent Systems, July/August 2004, www.mindswap.org/papers/IEEE-IS-04.pdf.
[176] 黄金才,陈文伟,田青等.决策支持系统可视化快速集成环境.国防科技大学学报,2000,22(3):118-122.
[177] 胡爱民.一种可视化模型库管理系统的开发策略和应用.重庆大学学报,2000,6(3):43-46.
[178] Web Services Description Language (WSDL) 2.0, 2004. http://www.w3.org/TR/2004/WD-wsdl20-primer-20041221/.
[179] UDDI. The UDDI Technical White Paper. http://www.uddi.org/, 2000.
[180] Soap version 1.2. http://www.w3.org/2000/xp/Group/.
[181] Berners-Lee T, Hendler J, Lassila O. The Semantic Web. Scientific American, 2001, 284(5): 34-43.
[182] 戴超凡,邓苏,刘青宝.基于COM的可视化集成环境的设计与实现.计算机工程与应用,2000,6:4-5.
[183] 王欣荣.基于语言评价信息的群决策理论与方法研究[博士学位论文].东北大学,2003.
[184] Herrera F, Herrera-Viedma E. Linguistic decision analysis: steps for solving decision problems under linguistic information. Fuzzy Sets and Systems, 2000, 115(1): 67-82.
[185] Zadeh L A. The concept of a linguistic variable and its applications to approximate reasoning. Part Ⅰ, Inform. Sci. 8 (1975) 199-249, Part Ⅱ, Inform. Sci. 8 (1975) 301-357, Part Ⅲ, Inform. Sci. 9 (1975) 43-80.
[186] Bonissone P P. A fuzzy sets based linguistic approach: theory and applications, in: M. M. Gupta, E. Sanchez (Eds.), Approximate Reasoning in Decision Analysis, North-Holland, Amsterdam, 1982, pp. 329-339.
[187] Bordogua G, Passi G. A fuzzy linguistic approach generalizing boolean information retrieval: a model and its evaluation, J. Amer. Soc. Inform. Sci. 1993, 44:70-82.
[188] Miller G A. The magical number seven or minus two: some limits on our capacity of processing information, Psychol. Rev. 1956, 63: 81-97.
[189] Bordogua G, Fedrizzi M, Passi G. A linguistic modelling of consensus in group decision making based on OWA operators, IEEE Trans. Systems Man Cybernetics, 1997, 27: 126-132.
[190] Delgado M, Herrera F, Herrera-Viedma E, et al. Combining linguistic and numerical information in group decision making, Inform. Sci. 1998, 7: 177-194.
[191] Yager R R. An approach to ordinal decision making, Internat. J. Approx. Reason, 1995, 12: 237-261.
[192] Lee H M. Group decision making using fuzzy sets theory for evaluating the rate of aggregative risk in software development, Fuzzy Sets and Systems, 1996, 80: 261-271.
[193] Bonissone P P, Decker K S. Selecting uncertainty calculi and granularity: an experiment in trading-off precision and complexity, in: L. H. Kanal, J. F. Lemmer (Eds.), Uncertainty in Artificial Intelligence, North-Holland, Amsterdam, 1986, pp. 217-247.
[194] Tong M, Bonissone P P. Linguistic solutions to fuzzy decision problems, Stud. Management Sci. 1984, 20: 323-334.
[195] Delgado M, Verdegay J L, Vila M. A. Linguistic decision making models, Internat. J. Intell. Systems, 1992, 7:479-492.
[196] Bonissone P P. A fuzzy sets based linguistic approach: theory and applications, in: M. M. Gupta, E. Sanchez (Eds.), Approximate Reasoning in Decision Analysis, North-Holland, Amsterdam, 1982, pp. 329-339.
[197] Torra V. Negation functions based semantics for ordered linguistic labels, Internat. J. Intell.
[2] Department of the Navy Acquisition Reform Office. Simulation Based Acquisition (SBA) status and international implications. http://www.msiac.dmso.mil/sba_documents/SBA%20status%20&%20internat'1%20imp.pdf, 2000, 9.
[3] Parker T. Final Report of the Acquisition Task Force on Modeling and Simulation. DDR&E Acquisition Task Force, Jun. 1994.
[4] Portmann H H. Study on the Application of Modeling and Simulation to the Acquisition of Major Weapon Systems. American Defense Preparedness Association (ADPA), Sep. 1996.
[5] Naval Research Advisory Committee. Naval Research Advisory Committee Report on Modeling and Simulation, NRAC 94-3, Nov. 1994.
[6] James E. Coolahan. A Simulation Based Acquisition Collaborative Environment for Strike Warfare, 6th Annual JAWS S3 Symposium and Exhibition, June 2000.
[7] Col Phil Faye. Simulation Based Acquisition Re-Engineering Acquisition for 2005 and Beyond, AFMC SBA, Dec. 2000.
[8] BDM Federal, Inc. Collaborative Virtual Prototyping Sector Study. North American Technology and Industrial Base Organization, May 1996.
[9] Patenaude A. Study on the Effectiveness of Modeling and Simulation in the Weapon System Acquisition Process. Oct. 1996.
[10] Forst R. Simulation Based Acquisition an Ongoing Look. 98F-SIW. 1998.
[11] DoD SBA Task Force. A Roadmap for Simulation Based Acquisition. http://www.msosa.dmso.mil/sba/documents.asp, 1998, 12.4.
[12] David S. The Role of System Modelling and Simulation in Royal Australian Navy Capability Management. DSTO-GD-0244. http://www.dsto.defence.gov.au/corporate/reports/, July 2000.
[13] LCdr J. United Kingdom National Experience in Simulation, Modelling and Synthetic Environments. NATO Modelling and Simulation Conference. Norfolk, Virginia, USA. October 1999.
[14] Vice-Chief of the Defence Staff Group. Modelling and Simulation: Enabling the Creation of Affordable, Effective 2020 Canadian Forces, http://www.vcds.dnd.ca/intro_e.asp, Apr. 2000.
[15] NATO Modelling and Simulation Master Plan. North Atlantic Treaty Organisation Document AC/323 (SGMS)D/2.www.drdc-rddc.dnd.ca/seco/documents, 7 August 1998.
[16] 李伯虎,王行仁,黄柯棣等.综合仿真系统研究.系统仿真学报,2000,12(5):429-434.
[17] 熊光楞,李伯虎等.虚拟样机技术.系统仿真学报,2001,13(1):114-117.
[18] 柴旭东,李伯虎,熊光楞等.复杂产品协同仿真平台的研究与实现.计算机集成制造系统—CIMS,2002,8(7):580-584.
[19] 郭斌,熊光楞,陈晓波.支持复杂产品设计的协同仿真平台研究.机械与电子,2002,4:26-29.
[20] 王江云,王行仁,贾荣珍.协同仿真环境体系结构.系统仿真学报,2001,13(6):687-689.
[21] 魏华梁,刘藻珍,李钟武.二十一世纪武器系统仿真新动向-基于仿真的采办与管理.计算机仿真,2000,17(4):24-28.
[22] 李伯虎,柴旭东,毛媛.现代仿真技术发展中的两个热点——ADS,SBA.系统仿真学报,2001,13(1):101-105.
[23] 黄柯棣等.略论军用仿真技术面临的需求与发展的方向.系统仿真学报.2001(1):6-10.
[24] 段红,黄柯棣.基于仿真的采办体系结构.系统仿真学报,2001,13(2):247-250.
[25] 段红,黄柯棣,李革.基于仿真的采办协同环境研究.系统仿真学报,2002,14(2):149-151.
[26] 王江云,林新,王行仁.基于HLA的SBA协同环境研究.计算机仿真,2001,18(5):7-9.
[27] Jacques S. Gansler. Life-Cycle Modeling and Simulation A Key Element in Acquisition Reform. http://www.acq.osd.mil/acqweb/usd/, 1998.
[28] James W. Hollenbach. Department of the Navy (DON) Corporate Approach to Simulation Based Acquisition (SBA). http://www.acq-ref.navy.mil/, 2000.
[29] Dahmann J. SBA Yesterday & Today: Current View of SBA in Advanced Systems Engineering and System-of-Systems Environment. http://www.dtic.mil/ndia/2002sba/dahmann.pdf, 2002.
[30] James W. Hollenbach. The Joint Strike Force (JSF) Distributed Product Description (DPD). http://www.sisostds.org/siw/, 2000.
[31] James W. Hollenbach. JSF Modeling Information Management. http://www.sisostds.org/siw/, 2000.
[32] Richard A. Reading, Pobat M. Common Threat Representation in Simulation and Testing of Ship Self Defense. http://www.sisostds.org/siw/, 2000.
[33] Frost R. Simulation Based Acquisition, The Initiative. www.msiac.dmso.mil/sba_documents/, 2001.
[34] Smith R. Simulation Based Acquisition. http://www.modelbenders.com/sba/, 1998.
[35] 戴汝为.21世纪组织管理途径的探讨.管理科学学报,1999,1(3):1-6.
[36] 成思危.复杂科学与系统工程.工管理科学学报,1999,2(2):1-7.
[37] 金吾伦,郭元林.复杂性科学及其演变.复杂系统与复杂性科学,2004,1(1):1-5.
[38] 戴汝为.复杂巨系统科学——一门21世纪的科学.自然杂志,1997,7(2):187-192.
[39] 钱学森,于景元,戴汝为.一个科学的新领域——开放的复杂巨系统及其方法论.自然杂志,1990,13(1):3-10.
[40] 钱学森.再谈开放的复杂巨系统.模式识别与人工智能,1991,4(1):5-8.
[41] 戴汝为,王珏,田捷.智能系统的综合集成.杭州:浙江科学技术出版社,1995.
[42] 戴汝为 操龙兵.综合集成研讨厅的研制.管理科学学报,2002,5(3):10-16.
[43] 钱学森.论系统工程.长沙:湖南科学技术出版社,1982.
[44] 钱学森.社会主义建设的总体设计部[A].创建系统学[M].太原:山西科学技术出版社,2001.134.
[45] 于景元,周晓纪.综合集成方法与总体设计部.复杂系统与复杂性科学,2004,1(1):20-26.
[46] 于景元,钱学森.关于开放的复杂巨系统的研究.系统工程理论与实践,1992,12(5):8-12.
[47] 戴汝为.从定性到定量的综合集成技术.模式识别与人工智能,1993,6(2):60-65.
[48] 王寿云等.开放的复杂巨系统.杭州:浙江科学技术出版社,1995.
[49] 艾克武,胡晓惠.综合集成的内容与方法——复杂巨系统问题研究.系统工程与电子技术,1998,7:17-23.
[50] 胡晓峰.系统集成与系统综合集成.测控技术,1999,18(9):11-13.
[51] 戴汝为.系统科学与思维科学交叉发展的硕果——大成智慧工程.系统工程理论与实践,2002,5:8-11.
[52] 于景元,刘毅.复杂性研究与系统科学.科学学研究,2002,20(5):449-453.
[53] 于景元,涂元季.从定性到定量综合集成方法——案例研究.系统工程理论与实践,2002,5:1-7.
[54] 于景元,周晓纪.从定性到定量综合集成方法的实现和应用.系统工程理论与实践,2002,10:26-32.
[55] 苗东升.综合集成法的认识论基础.系统辨证学学报,2003,11(1):37-42.
[56] 王丹力,戴汝为.综合集成研讨厅体系中专家群体行为的规范.管工管理科学学报,2001,4(2):1-6.
[57] 崔霞,戴汝为,李耀东.群体智慧在综合集成研讨厅体系中的涌现.系统仿真学报,2003,15(1):146-153.
[58] 崔霞,李耀东,戴汝为.HWME中基于学习型组织的专家有效互动对话模型.管理科学学报,2004,7(2):80-87.
[59] 操龙兵,戴汝为.基于Internet的综合集成研讨厅系统体系结构.计算机科学,2002,29(6):6-66.
[60] 操龙兵,戴汝为.综合集成研讨厅的软件体系结构.软件学报,2002,13(8):1430-1435.
[61] 鲁东明,张晓宇,潘云鹤.基于知识碰撞模型的虚拟研讨厅系统.计算机研究与发展,2002,39(12):1720-1727.
[62] 胡晓峰,司光亚.战略决策综合集成研讨环境SDE98的体系结构.小型微型计算机系统,1999,20(2)88-91.
[63] 胡晓峰,司光亚,吴琳等.SDS2000-一个定性定量结合的战略决策综合集成研讨与模拟环境.系统仿真学报,2000,12(6):595-599.
[64] 司光亚.战略决策综合集成研讨与模拟环境与实现[博士学位论文].长沙:国防科技大学,2000.
[65] 王丹力,戴汝为.群体一致性及其在研讨厅中的应用.系统工程与电子技术,2001,23(7):33-37.
[66] 顾基发.意见综合—怎样达成共识.系统工程学报,2001,16(5):340-348.
[67] 孙景乐,张朋柱.一种互补的研讨框架的设计与实现.系统工程学报,2001,16(5):360-365.
[68] 程少川,张朋柱,卢明德.群体过程信息的树状结构及其定性收敛的研究.系统工程学报,2001,16(5):371-375.
[69] 彭本红,孙绍荣,张文健.研讨厅中专家意见的可靠性研究.系统工程理论方法应用,2004,13(4):343-346.
[70] The Consensus Building Institute, http://www.cbi-web.org/home.htm, 2002.
[71] 唐锡晋.模型集成.系统工程学报,2001,16(5):322-329.
[72] 胡代平,王浣尘.基于多Agent的模型系统研究.系统工程理论方法应用,2001,10(2):89-92.
[73] Chari K. Model composition in a distributed environment. Decision Support Systems, 2003, 35: 399-413.
[74] 毛海军,唐焕文,李飞.宏观经济智能预测决策支持系统模型系统的Agent实现研究.计算机工程与应用,2003,15:77-79.
[75] 谢勇,王红卫.基于逆向推理策略的模型集成.计算机集成制造系统—CIMS,2002,8(9):690-694.
[76] 谢勇,王红卫.模型集成及其优化策略.计算机集成制造系统—CIMS,2005,11(1):58-62.
[77] 司光亚,胡晓峰.战略决策模拟环境中XOD综合集成机制的研究与实现.小型微型计算机系统,2002,23(2):242-245.
[78] 杨镜宇,吴琳,司光亚等.战争系统中面向按需服务的仿真资源综合集成问题研究.系统仿真学报,2003,15(12):1683-1686.
[79] 王黎明,毛汉英.区域可持续发展综合集成研讨厅体系研究.地理研究,1998,17(4): 408-414.
[80] 常显奇等.空间军事系统综合集成研讨厅内容体系的研究与建设.系统工程理论与实践,2001,6(5):86-90.
[81] 胡代平,王浣尘.基于Agent的宏观经济决策支持系统.系统工程理论与实践,2001,1:33-37.
[82] Cao L B, Dai R w. Autonomous intelligent agents for metasynthetic engineering: a macroeconomic decision support system. First International Congress on Autonomous Intelligent Systems(1CAIS2002), Geelong, Australia, 2002.
[83] 张景涛,王丹力,王宏安等.敏捷供应链管理的综合集成研讨厅.系统工程学报,2003,18(6):515-520.
[84] 吴晓伟,徐福缘,吴伟昶.基于“综合集成研讨厅”的企业竞争情报系统研究.情报学报,2004,23(6):746-754.
[85] Dolk D R. Model Integration and a Theory of Models. Decision Support Systems, 1993, 9:51-63.
[86] Lenard M L. An Object-Oriented Approach to Model Management. Decision Support Systems, 1993, 9 (1): 67-73.
[87] Ling T P, Konsynski B. Modeling by Analogy: Use of Analogical Reasoning in Model Management Systems. Decision Support Systems, 1993, 9:113-125.
[88] Liang T P. Analogical Reasoning and Case-based Learning in Model Management. Decision Support Systems, 1993, 10: 137-160.
[89] Muhanna W A. An Object-Oriented Framework for Model Management and DSS Development. Decision Support Systems, 1993, 9: 217-229.
[90] Basu A, Blanning R W. Model Integration Using Metagraphs. Information Systems Research, 1994, 5(3): 195-218.
[91] Muhanna W A, Pick R A. Meta-Modeling Concepts and Tools for Model Management: A Systems Approach. Management Science, 1994, 40(9): 1093-1123.
[92] 周宽久,黄梯云.面向对象的模型表示与模型复合.哈尔滨工业大学学报,1997,29(4):18-20.
[93] Andrea E. Rizzoli J. Davis R, et al. Model and Data Integration and Re-use in Environmental Decision Support Systems. Decision Support Systems, 1998, 24(2):127-144.
[94] 王林,高国安.面向对象的IDSS模型库系统的构造.电脑与信息技术,2000,(1):1-5.
[95] 杜江,孙玉芳.基于面向对象模型库的DSS可重用体系结构研究.系统工程理论与实践,2000,(1):1-6.
[96] 黄跃进,反伟胜,朱云龙.空间决策支持系统模型库系统研究.信息与控制,2000,29(3):219-224.
[97] 赵新昱,陈文伟,张维明等.基于构件的决策支持系统中模型组织集成框架IFMO.国防科技大学学报,2001,23(2):61-65.
[98] Henderson S. The Design and Development of a Flexible Component-based Decision Support System Generator. A research essay presented to the University of Auckland in partial fulfilment of the requirements for the Degree of BCom(Hons) in Management Science and Information Systems. December 2001.
[99] 马金平.基于ActiveX组件技术的模型库系统的开发研究.计算机应用,2001,20(5):33-35.
[100] 魏继才,董文洪,胡晓峰等.智能决策系统中模型服务器的设计与实现.计算机仿真,2003,20(1):22-24.
[101] 魏继才,胡晓峰,范波涛等.综合集成决策模拟系统中模型的设计与实现.计算机仿真,2003,20(1):25-28.
[102] 彭英武,严建钢,司光亚等.分布式环境中模型服务实现中的若干关键技术.计算机应用.2003,23(5):58-61.
[103] 林杰,张丽峰,薛行.基于UDDI的分布模型管理.计算机集成制造系统—CIMS,2004,10(3):276-280.
[104] 林杰,雷星晖,王效俐.基于Web服务的分布模型管理系统的研究.计算机应用,2004,24(4):80-82.
[105] 张振兴,王翠茹,刘建峰等.基于Web服务的模型库系统的研究与实现.华北电力大学学报,2003,30(4):78-81.
[106] 黄卓,张涛,郭波.基于Web Service的分布模型管理方法研究.计算机工程与设计,2004,25(3):379-380.
[107] 周昭权,薛永生,黄震华.基于Web Service的DSS模型重用机制研究.厦门大学学报,2004,43(6):776-781.
[108] Byung Kwon O. Meta web service: building web-based open decision support system based on web services. Expert Systems with Applications, 2003, 24: 375-389.
[109] 王慧斌、徐小群.综合集成研讨厅体系及应用研究.信息与控制,2001,30(6):516-521.
[110] 张朋柱,刁石京.我国政府宏观决策任务的分类研究.系统工程学报,2001,16(5):354-359.
[111] 沈惠璋,王浣尘.基于演化模型的宏观经济系统分析方法.系统工程学报,2001,16(5):389-393.
[112] 葛新元,王大辉,袁强等.多部门经济动力学模型及其合理性分析.系统工程学报,2001, 16(5):397-401.
[113] 舒光复.综合集成系统重构及宏观经济研究中的应用.系统工程学报,2001,16(5):349-353.
[114] The Consensus Building Institute. http://www.cbuilding.org/consensus/index.html, 2005-4-10.
[115] Leher K, Wagner C. Rational consensus in science and society. Dordecht: Reidel, 1981.
[116] Schuman S, Richardson J. Decision conferencing for systems planning. Information and Management, 1991, 21:147-159.
[117] Lawrence Butler C T. Amy Rothstein. The book On Conflict and Consensus, http://www.wandreilagh.org/consensus.pdf, 2005.
[118] Consensus Technology. The art and science of collaborative decision making. http://www.consensustech.com/, 2005.4.10.
[119] Consensus-How to and Why. http://www.msu.edu/～corcora5/org/consensus.html.
[120] The Team Resource Center Servies. http://www.team-creations.com/Services/meeting.htm.
[121] Hiltz S R, Turoff M, et al. Distributed group support systems: theory development and experimentation[A]. Coordination theory and collaboration technology[M]. Erlbaum Associates, 1996.
[122] DeGroot M H. Reaching a consensus. Journal of the American Statistical Association, 1974, 69:118-212.
[123] Kacprzyk J, Nurmi H, Fedrizzi M. Consensus under fuzziness. Dordrecht: Kluwer Academic Publishers, 1997.
[124] Kacprzyk J, Fedrizzi M, Nurmi H. "Soft" degrees of consensus under fuzzy preference and fuzzy majorities[A]. Consensus under fuzziness[M]. Dordrecht: Klawer Academic Publishers, 1997, 55-82.
[125] Zadrozny S. An approach to the consensus reaching support in fuzzy environment [A]. Consensus under fuzziness [M]. Dordrecht: Klawer Academic Publishers, 1997. 83-109.
[126] Seo F. Construction of fuzzy utility function in group decision making[A]. Consensus under fuzziness[M]. Dordrecht: Klawer Academic Publishers, 1997. 211-230.
[127] Herrera F, Hrrera-Viedma E, Verdegay J L. A model of consensus in group decision making under linguistic assessments. Fuzzy Sets and Systems, 1996, 79: 73-87.
[128] Herrera F, Herrera-Viedma E, Verdegay J L. A rational consensus model in group decision making using linguistic assessments. Fuzzy Sets and Systems, 1997, 88: 31-49.
[129] 王丹力,戴汝为.群体一致性及其在研讨厅中的应用.系统工程与电子技术,2001,7:33-37.
[130] 涂承胜,鲁明羽,陆玉昌.Web挖掘研究综述.计算机工程与应用,2003,(10):90-93.
[131] Enriching Representations of Work to Support Organisational Learning, http://kmi.open.ac.uk/projects/enrich/, 2005-04-10.
[132] Mulholland P, Zdrahal Z, Domingue J A, et al. A Methodological Approach to Supporting Organizational Learning. International Journal of Human-Computer Studies, 2001, 55(3): 337-367.
[133] Mulholland P, Domingue J, Zdrahal Z, et al. Organisational Learning: An Overview of the Enrich Approach. Journal of Information Services and Use, 2000, 20(1): 9-23.
[134] The ClockWork Project, http://kmi.open.ac.uk/projects/clockwork/, 2005-4-10.
[135] Mulholland P, Zdrahal Z, Sainter P, et al. Supporting the sharing and reuse of modelling and simulation engineering knowledge. International Conference on Concurrent Enterprising (ICE2003), Espoo, Finland, 16-18 June.
[136] Zdrahal Z, Mulholland P, Valasek M, Sainter P, Koss, et al. A toolkit and methodology to support the collaborative development and reuse of engineering models. Database and Expert Systems Applications Conference (DEXA 2003), Prague, Czech Republic.
[137] Mizoguchi R, Kitamura Y, Arai E, et al. A Methodology of Collaborative Synthesis by Artificial Intelligence http://www.ei.sanken.osaka-u.ac.jp/pub/miz/miz-skfcw99.pdf.
[138] http://new-humanity.narod.ru.
[139] Sandelowski. M, Barroso J. Writing the Proposal for a Qualitative Research Methodology Project. Qualitative Health Research, 2003, 13: 781-820.
[140] Sandelowski. M, Barroso J. Reading Qualitative Studies, International Journal of Qualitative Methods, 2002, 1(1), Article 5. http://www.ualberta.ca/～ijgm/.
[141] 常鑫,殷红海.Daniel Kahneman与行为经济学.http://www.psychcn.com/psyhistory/200502/1650311539.shtml.
[142] Jams W. Hollenbach. Collabrative Achievement of Advanced Acquisition Environments, September 2001, http://www.acq-ref.navy.mil/reflib/.
[143] 李明,刘澎.武器装备发展系统论证方法与应用[M].北京:国防工业出版社,2000.
[144] Peggy D. Gravitz, Sheehan J, McLean T. Common activities in Data Interchange Format (DIF) development, http://www.sisostds.org/doclib/doclib.cfm?SISO_RID_1000944,1999, 2.3.
[145] 王鹏,李伯虎,柴旭东等.复杂产品虚拟样机协同仿真建模技术研究.系统仿真学报,2004,16(2):274-277.
[146] 张建明.基于仿真的采办若干关键理论和技术研究[博士学位论文].南京,南京理工大学,2004.11
[147] 操龙兵,戴汝为.综合集成与决策[J].计算机研究与发展,2003,40(4):531-537.
[148] Carlsson C, Turban E. DSS: directions for the next decade (Introduction of the journal Decision Support Systems). Decision Support Systems, 2002, 33(2): 105-110.
[149] 胡晓惠.研讨厅系统实现方法及技术的研究.系统工程理论与实践,2002,(6):1-10.
[150] 陈文伟.决策支持系统及其开发.北京:清华大学、广西科学技术出版社,2000.
[151] Peltonen H. Concepts and an Implementation for Product Data Management[Doctor thesis]. Helsinki: Department of Computer Science and Engineering, Helsinki University of Technology, 2000.
[152] 王博,晓龙.面向对象的建模设计技术与方法.北京:学苑出版杜,1993.
[153] Page-Jones M.UML面向对象设计基础.北京:人民邮电出版社,2001.
[154] 黄海量.产品开发网络化协同决策方法与使能技术研究[博士学位论文].西安:西安交通大学,2002.
[155] Extensible Markup Language (xml) 1.0 (second edition), http://www.w3.org/XML.
[156] Tsalgatidou A, Pilioura T. An Overview of Standards and Related Technology in Web Services. Distributed and Parallel Databases, 2002, 12 (2-3): 135.
[157] Benatallah B, Dumas M, Fauvet M C, et al. Towards Patterns of Web Services Composition. In S. Gorlatch and F. Rabhi, editors, Patterns and Skeletons for Parallel and Distributed Computing. Springer Verlag, UK, Nov. 2002.
[158] Lee K W, Huh S Y. Model-Solver Integration in Decision Support Systems: A Web Services Approach. http://mis.temple.edu/sigdss/icis03/proceedings/DSSWorkshop03-Lee.pdf, 2003.
[159] W3C Web Services Activity. http://www.w3.org/2002/ws/.
[160] Web Service Choreography Interface (WSCI) 1.0, 8 August 2002. http://www.w3.org/TR/wsci/.
[161] Business Process Execution Language for Web Services version 1.1, May 2003. http://www-128.ibm.com/developerworks/library/specification/ws-bpel/.
[162] Lee T B. Semantic Web Architecture. http://www.w3.org/2000/talks/1206-xml2k-tbl/slide10-0.html, 2001-07-20.
[163] OWL-S Coalition. OWL-S 1.1 release, http://www.daml.org/services/owl-s/1.1/.
[164] Wu D, Parsia B, Sirin E, et al. Automating DAML-S Web Services Composition Using SHOP2. www.mindswap.org/papers/ISWC03-SHOP2.pdf, 2003.
[165] Paolucci M, Kawamura T, Terry R. Payne, et al. Semantic Matching of Web Services Capabilities. In International Semantic Web Conference, Sardinia, Italy, June 9-12, 2002.
[166] Akash M, Bercovier M, Marowka A, et al. Towards Virtualization of On-Demand Web Service Composition Using an Improved Ranking Algorithm. Proceedings of the International Symposium on Web Services & Applications, ISWS'04, Las Vegas, Nevada, USA, June 21-24, 2004. http://scom.hud.ac.uk/scomzl/conference/chenhua/040528_01E/ISW2037.pdf.
[167] Dale J, Ceccaroni L. Pizza and a Movie: A Case Study in Advanced Web Services. Proceedings of the workshop AAMAS 2002-W04: Challenges in Open Agent Systems. http://www.nar.fujitsulabs.com/documents/fla-nartm02-03.pdf.
[168] 蔡铭、林兰芬、董金祥.网络化制造环境中制造服务智能匹配技术研究.计算机辅助设计与图形学学报,2004,16(8):1090-1096.
[169] 张蓉、申德荣等.基于本体的Web服务查找与合成技术研究.计算机集成制造系统—CIMS,2003,9(10):922-925.
[170] Sirin E, Hendler J, Parsia B. Semi-automatic Composition of Web Services using Semantic Descriptions. http://www.mindswap.org/papers/composition.pdf, 2003.
[171] Lin M S, Guo H O, Yin J F. Goal Description Language for Semantic Web Service Automatic Composition. Proceedings of the 2005 Symposium on Applications and the Internet (SAINT'05). http://doi.ieeecomputersociety.org/10.1109/SAINT.2005.33.
[172] Aversano L, Canfora G, Ciampi A. An algorithm for Web service discovery through their composition. Proceedings of the IEEE International Conference on Web Services (ICWS'04), June 6-9, 2004, San Diego, California, USA.
[173] Seyyed V. Hashemian, Mavaddat F. A Graph-Based Approach to Web Services Composition. Proceedings of the 2005 Symposium on Applications and the Internet (SAINT'05). http://doi.ieeecomputersociety.org/10.1109/SAINT. 2005.4
[174] Alfaro L, Henzinger T A. Interface Automata, Proceedings of the 8th European software engineering conference held jointly with 9th ACM SIGSOFT international symposium on Foundations of software engineering, ACM Press, pp. 109-120, 2001.
[175] Sirin E, Parsia B, Hendler J. Filtering and Selecting Semantic Web Services with Interactive Composition Techniques. IEEE Intelligent Systems, July/August 2004, www.mindswap.org/papers/IEEE-IS-04.pdf.
[176] 黄金才,陈文伟,田青等.决策支持系统可视化快速集成环境.国防科技大学学报,2000,22(3):118-122.
[177] 胡爱民.一种可视化模型库管理系统的开发策略和应用.重庆大学学报,2000,6(3):43-46.
[178] Web Services Description Language (WSDL) 2.0, 2004. http://www.w3.org/TR/2004/WD-wsdl20-primer-20041221/.
[179] UDDI. The UDDI Technical White Paper. http://www.uddi.org/, 2000.
[180] Soap version 1.2. http://www.w3.org/2000/xp/Group/.
[181] Berners-Lee T, Hendler J, Lassila O. The Semantic Web. Scientific American, 2001, 284(5): 34-43.
[182] 戴超凡,邓苏,刘青宝.基于COM的可视化集成环境的设计与实现.计算机工程与应用,2000,6:4-5.
[183] 王欣荣.基于语言评价信息的群决策理论与方法研究[博士学位论文].东北大学,2003.
[184] Herrera F, Herrera-Viedma E. Linguistic decision analysis: steps for solving decision problems under linguistic information. Fuzzy Sets and Systems, 2000, 115(1): 67-82.
[185] Zadeh L A. The concept of a linguistic variable and its applications to approximate reasoning. Part Ⅰ, Inform. Sci. 8 (1975) 199-249, Part Ⅱ, Inform. Sci. 8 (1975) 301-357, Part Ⅲ, Inform. Sci. 9 (1975) 43-80.
[186] Bonissone P P. A fuzzy sets based linguistic approach: theory and applications, in: M. M. Gupta, E. Sanchez (Eds.), Approximate Reasoning in Decision Analysis, North-Holland, Amsterdam, 1982, pp. 329-339.
[187] Bordogua G, Passi G. A fuzzy linguistic approach generalizing boolean information retrieval: a model and its evaluation, J. Amer. Soc. Inform. Sci. 1993, 44:70-82.
[188] Miller G A. The magical number seven or minus two: some limits on our capacity of processing information, Psychol. Rev. 1956, 63: 81-97.
[189] Bordogua G, Fedrizzi M, Passi G. A linguistic modelling of consensus in group decision making based on OWA operators, IEEE Trans. Systems Man Cybernetics, 1997, 27: 126-132.
[190] Delgado M, Herrera F, Herrera-Viedma E, et al. Combining linguistic and numerical information in group decision making, Inform. Sci. 1998, 7: 177-194.
[191] Yager R R. An approach to ordinal decision making, Internat. J. Approx. Reason, 1995, 12: 237-261.
[192] Lee H M. Group decision making using fuzzy sets theory for evaluating the rate of aggregative risk in software development, Fuzzy Sets and Systems, 1996, 80: 261-271.
[193] Bonissone P P, Decker K S. Selecting uncertainty calculi and granularity: an experiment in trading-off precision and complexity, in: L. H. Kanal, J. F. Lemmer (Eds.), Uncertainty in Artificial Intelligence, North-Holland, Amsterdam, 1986, pp. 217-247.
[194] Tong M, Bonissone P P. Linguistic solutions to fuzzy decision problems, Stud. Management Sci. 1984, 20: 323-334.
[195] Delgado M, Verdegay J L, Vila M. A. Linguistic decision making models, Internat. J. Intell. Systems, 1992, 7:479-492.
[196] Bonissone P P. A fuzzy sets based linguistic approach: theory and applications, in: M. M. Gupta, E. Sanchez (Eds.), Approximate Reasoning in Decision Analysis, North-Holland, Amsterdam, 1982, pp. 329-339.
[197] Torra V. Negation functions based semantics for ordered linguistic labels, Internat. J. Intell.