城市配网规划的优化算法、评价体系与智能技术的研究
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摘要
随着国民经济的快速发展,我国输配电发展不平衡问题逐步显现出来,配电网中存在的问题在城市电网得到了集中地体现。本文结合城市发展规划,改进了电网规划的数学模型;研究了新型生物启发式优化算法的机理及其在电网规划中的应用;采用先进的软件研发理念设计了基于GIS的城市电网智能规划系统;研究了配电自动化系统的通信方式选择和信息安全问题,并提出了各自的评价体系和评价方法。这些问题的提出和解决为城市电网优化规划提供了科学的方法和实用的工具。论文成果概括为以下几点:
1.研究城市电网规划中变电站选址、定容问题的数学模型和算法,以变电站容量和供电半径为罚函数、以地理可行性为约束条件,改进了变电站规划的经济性模型;提出了大城市两个电压等级联合规划的数学模型。计算结果表明所提出的模型提高了城市电网变电站规划的经济性、负载的均衡性和地理的实用性。
2.针对一种新的优化算法-细菌群体趋药性优化算法进行了深入的研究。验证了群体控制参数对BCC算法性能的影响,并提出了算法应用的参数控制策略。改进算法中采用了自适应调整感知范围、当细菌确定下一步位置时增加微分进化的待选个体和采用混沌迁移机制等改进措施,增强了算法跳出局部最优解的能力,新算法的全局搜索能力得到显著提高。
3.结合规划领域最近的理论成果,提出了构建集数据管理和智能规划为一体的企业配电网智能规划平台的设计思想。汲取了国外大型软件的开发经验,设计了基于COTS构件的软件体系结构,提高了软件的复用率和应用的灵活性。文中给出了系统的体系架构设计、业务处理逻辑设计、功能设计、接口设计及软件的实现模型。该软件已完成,并通过了山东省科技厅鉴定。
4.针对配电自动化系统多种通信方式的选择问题,提出了定性与定量相结合的多指标无线通信方式的评价指标体系,它包括经济性、可靠性和技术性三类指标。利用带偏好的数据包络分析方法对评价单元进行综合效益评价。评价结果为配电通信方式的选择提供了科学的依据。
5.在国家自然科学基金项目(50877026)的支持下,研究了配电自动化系统的信息安全问题,参照信息安全评估标准ISO/IEC 17799:2005,构建了一套全面反映配电自动化系统信息安全等级的评价指标体系。提出了基于改进的D-S证据理论和模糊层次分析法的配电自动化系统信息安全的评价方法。评价结果对配电自动化系统的安全运行管理和项目建设具有科学的指导意义。
With the rapid development of national economy,the problem of development unbalance in power transmission system and distribution system gradually emerged,and the problems existing in distribution network have been expressed focused on urban power grid.In this paper,optimization planning method and mathematical model for urban power grid planning are improved integrating with urban development planning.A new biological heuristic optimization algorithm mechanism and its application in power grid planning are researched. By using the advanced idea of software development,a scientific and practical urban power grid intelligent planning system based on GIS is designed and developed.The issues of information security and selecting communication means in distribution automation system are researched,and the respective assessment index system and method are presented.The solution of these proposed problems provide scientific methods and practical tools for urban power grid optimization planning.Thesis results summarized as follows:
1.Study the mathematical models and optimization algorithms of substation planning in urban power grid planning,take transformer substation capacity and power supply radius as penalty function,geographical feasibility as constraint condition to improve the economic model of substation planning,and propose the mathematical model of two-level voltages united planning in big city.The calculation results show that the model proposed improved the economics of urban power grid planning,the balance of transformer substation load and practicality in geography of transformer substations positions.
2.A new colony intelligence optimization Algorithm—Bacterial Colony Chemotaxis algorithm(BCC) is researched deeply.The influence of the colony control parameter to the performance of BCC is studied,and the control strategies of parameters are proposed.The basic BCC algorithm has the problem of local minimum,therefore,in the improved algorithm some improvements,for example adjusting the perception scope self-adaptively,adding differential evolutionary individual while the bacteria choice next location and taking Chaos Transfer mechanism are adopted,and the ability to get rid of the local optimum is greatly improved.The experimental results show that the new algorithm improves the global optimization performance.Research results lay the foundations for further study.Applying the algorithm to substation planning obtains good result.
3.Combining the advanced theoretical harvests in recent years in the field of planning, design idea of urban power network intelligent planning platform which integrates data management and intelligent planning is proposed.Learning from foreign experience in large-scale software development,three-layer software architecture basing on COTS components technology is designed,which proposes the multiplexing ratio and the application flexibility of the software.The architecture design,the business process logic design,the function design,interface design,algorithm design and the implementary model of the system are presented.The software has been completed,and gains Science & Technology Achievement Certificate via appraisal of experts of Shandong Province Science and Technology Hall Organization.This Project generally reaches the international advanced level.
4.As to the problem of selecting communication means in distribution automation system(DAS),an multi-index evaluation system which combines the qualitative and quantitative analysis together to evaluate different wireless communication means is established,including three factors that are economy,reliability and technology.At the same time the Preferable Data Envelopment Analysis(DEA) method is applied to comprehensive evaluate the benefit of the evaluated unit,the communication means which has the highest benefit index will be selected as the preferred means.The evaluation result provides scientific evidence for selecting the communication network of DAS.
5.With the support of the National Natural Science Foundation Project(50877026), information security of distribution automation system is studied.According to information security assessment standard ISO/IEC 17799:2005,analyzes the indices,which affect the information security levels of assets,and establish an evaluation index system which reflects information security risk levels comprehensively from multi-hierarchy and multi-attribute. Assessment method of information security levels in DAS based on FAHP and improved D-S evidence theory is presented.The assessment result has feasibility and guidance in DAS safe operation management and project construction.
1.研究城市电网规划中变电站选址、定容问题的数学模型和算法,以变电站容量和供电半径为罚函数、以地理可行性为约束条件,改进了变电站规划的经济性模型;提出了大城市两个电压等级联合规划的数学模型。计算结果表明所提出的模型提高了城市电网变电站规划的经济性、负载的均衡性和地理的实用性。
2.针对一种新的优化算法-细菌群体趋药性优化算法进行了深入的研究。验证了群体控制参数对BCC算法性能的影响,并提出了算法应用的参数控制策略。改进算法中采用了自适应调整感知范围、当细菌确定下一步位置时增加微分进化的待选个体和采用混沌迁移机制等改进措施,增强了算法跳出局部最优解的能力,新算法的全局搜索能力得到显著提高。
3.结合规划领域最近的理论成果,提出了构建集数据管理和智能规划为一体的企业配电网智能规划平台的设计思想。汲取了国外大型软件的开发经验,设计了基于COTS构件的软件体系结构,提高了软件的复用率和应用的灵活性。文中给出了系统的体系架构设计、业务处理逻辑设计、功能设计、接口设计及软件的实现模型。该软件已完成,并通过了山东省科技厅鉴定。
4.针对配电自动化系统多种通信方式的选择问题,提出了定性与定量相结合的多指标无线通信方式的评价指标体系,它包括经济性、可靠性和技术性三类指标。利用带偏好的数据包络分析方法对评价单元进行综合效益评价。评价结果为配电通信方式的选择提供了科学的依据。
5.在国家自然科学基金项目(50877026)的支持下,研究了配电自动化系统的信息安全问题,参照信息安全评估标准ISO/IEC 17799:2005,构建了一套全面反映配电自动化系统信息安全等级的评价指标体系。提出了基于改进的D-S证据理论和模糊层次分析法的配电自动化系统信息安全的评价方法。评价结果对配电自动化系统的安全运行管理和项目建设具有科学的指导意义。
With the rapid development of national economy,the problem of development unbalance in power transmission system and distribution system gradually emerged,and the problems existing in distribution network have been expressed focused on urban power grid.In this paper,optimization planning method and mathematical model for urban power grid planning are improved integrating with urban development planning.A new biological heuristic optimization algorithm mechanism and its application in power grid planning are researched. By using the advanced idea of software development,a scientific and practical urban power grid intelligent planning system based on GIS is designed and developed.The issues of information security and selecting communication means in distribution automation system are researched,and the respective assessment index system and method are presented.The solution of these proposed problems provide scientific methods and practical tools for urban power grid optimization planning.Thesis results summarized as follows:
1.Study the mathematical models and optimization algorithms of substation planning in urban power grid planning,take transformer substation capacity and power supply radius as penalty function,geographical feasibility as constraint condition to improve the economic model of substation planning,and propose the mathematical model of two-level voltages united planning in big city.The calculation results show that the model proposed improved the economics of urban power grid planning,the balance of transformer substation load and practicality in geography of transformer substations positions.
2.A new colony intelligence optimization Algorithm—Bacterial Colony Chemotaxis algorithm(BCC) is researched deeply.The influence of the colony control parameter to the performance of BCC is studied,and the control strategies of parameters are proposed.The basic BCC algorithm has the problem of local minimum,therefore,in the improved algorithm some improvements,for example adjusting the perception scope self-adaptively,adding differential evolutionary individual while the bacteria choice next location and taking Chaos Transfer mechanism are adopted,and the ability to get rid of the local optimum is greatly improved.The experimental results show that the new algorithm improves the global optimization performance.Research results lay the foundations for further study.Applying the algorithm to substation planning obtains good result.
3.Combining the advanced theoretical harvests in recent years in the field of planning, design idea of urban power network intelligent planning platform which integrates data management and intelligent planning is proposed.Learning from foreign experience in large-scale software development,three-layer software architecture basing on COTS components technology is designed,which proposes the multiplexing ratio and the application flexibility of the software.The architecture design,the business process logic design,the function design,interface design,algorithm design and the implementary model of the system are presented.The software has been completed,and gains Science & Technology Achievement Certificate via appraisal of experts of Shandong Province Science and Technology Hall Organization.This Project generally reaches the international advanced level.
4.As to the problem of selecting communication means in distribution automation system(DAS),an multi-index evaluation system which combines the qualitative and quantitative analysis together to evaluate different wireless communication means is established,including three factors that are economy,reliability and technology.At the same time the Preferable Data Envelopment Analysis(DEA) method is applied to comprehensive evaluate the benefit of the evaluated unit,the communication means which has the highest benefit index will be selected as the preferred means.The evaluation result provides scientific evidence for selecting the communication network of DAS.
5.With the support of the National Natural Science Foundation Project(50877026), information security of distribution automation system is studied.According to information security assessment standard ISO/IEC 17799:2005,analyzes the indices,which affect the information security levels of assets,and establish an evaluation index system which reflects information security risk levels comprehensively from multi-hierarchy and multi-attribute. Assessment method of information security levels in DAS based on FAHP and improved D-S evidence theory is presented.The assessment result has feasibility and guidance in DAS safe operation management and project construction.
引文
[1]杨期余.配电网络.北京:中国电力出版社,1998
[2]H.L.Willis,H.Tram,M.V.Engel,et al.Optimization Applications to Power Distribution.IEEE Computer Applications in Power,1995,18(4):25-31
[3]王平洋.迎接新世纪的挑战—电力系统的新动向.电网技术,1998,22(11):1-3
[4]周湶.基于GIS的配电网规划智能决策支持系统及其算法的研究:[博士学位论文].重庆:重庆大学电气工程专业,2004
[5]范超,陆融,余建平.配电网规划后评估系统的研究与开发.华东电力,2007,35(12):57-59
[6]汤亚芳,王建民,程浩忠,等.配电网经济性综合评估体系.电网技术,2007,31(2):127-130
[7]牛东晓,曹树华,赵磊,等.电力负荷预测技术.北京:中国电力出版社,1998
[8]黄伟,费维刚.模糊理论在中长期负荷预测中的应用.电力系统及其自动化学报,1999,11(4):25-29
[9]Peng T.M.,Hubele N.F.,Karady G.G.Advancement in the Application of Neural Network for Short-term Forecasting.Transactions on Power System,1992,7(1):250-257
[10]袁明友,肖先勇,杨洪,等.基于灰色理论的供电系统负荷中长期预测模型及其应用.四川大学学报,2003,34(4):121-124
[11]Willis H L.Spatial Electric Load Forecasting.New York:MarcelDekker,Inc,2002
[12]Chow M Y,Tram H.Application of Fuzzy Multi-objective Decision Making in Spatial Load Forecasting.IEEE Transactions on Power System,1997,12(3):1360-1366
[13]Chow M Y,Tram H.Application of Fuzzy Multi-objective Decision Making in Spatial Load Forecasting.IEEE Transactions on Power Systems,1998,13(3):1360-1366
[14]王天华,王平洋,范明天.遗传算法、模糊逻辑和运输模型在配电网空间负荷预测中的应用.电网技术,1999,23(1):24-28
[15]Lei Shaolan,Sun Caixin,Zhou Quan,et al.Application of Fuzzy Rough Set Theory in Spatial Load Forecasting.Power System Technology,2005,29(9):26-30(in Chinese)
[16]Yu Yixin,Zhang Chongjian,Zhang Hongpeng.Small Area Land-use Analysis in Fuzzy Spatial Load Forecasting Part One Principle.Automation of Electric Power Systems,2001,25(7):23-26(in Chinese)
[17]Wu Bei,Ding Ming,Chen Minjiang.Spatial Load Forecasting Based on Fuzzy Reasoning Multi-objective Programming.Power System Technology,2004,28(15):48-52(in Chinese)
[18]Miranda V,Monteiro C.Fuzzy Inference in Spatial Load Forecasting.In:Halifax,Nova Scotia,eds.Proceedings of IEEE Power Engineering Society Winter Meeting Winter.Canada,2000:1063-1068
[19]Cheng Qiyun,Zhang Xiaoxing,Lei Shaolan,et al.Spatial Load Forecasting Method for Distribution Net Based on Rough Set Data Mining Approach.Transaction of China Electrotechnical Society,2005,20(5):98-102(in Chinese)
[20]Lei Shaolan,Sun Caixin,Zhou Lin,et al.Application of Attribute Reduct Method in Spatial Load Forecasting.Journal of Chongqing University,2004,27(3):85-88(in Chinese)
[21]Wu Bin,Chen Zhangchao,Bao Hailong.Spatial Electric Load Forecasting Based on Artificial Neural Networks and Fuzzy Algorithm.Power System Technology,1999,23(11):1-4(in Chinese)
[22]Wu H C,Lu C N.A Data Mining Approach for Spatial Modeling in Small Area Load Forecast.IEEE Transactions on Power System,2002,17(2):516-521
[23]程浩忠,高赐威,马则良.多目标电网规划的一般最优化模型.上海交通大学学报,2004,38(8):1229-1233
[24]葛少云,李慧,刘洪.基于加权Voronoi图的变电站优化规划.电力系统自动化,2007,31(3):29-34
[25]牛卫平,刘自发,张建华,等.基于GIS和微分进化算法的变电站选址定容.电力系统自动化,2007,31(18):82-86
[26]刘自发,张建华.基于改进多组织粒子群体优化算法的配电网络变电站选址定容.中国电机工程报,2007,27(01):107-111
[27]周敏,程浩忠,周中明.优化理论在城市配电网变电站选址中的应用.供用电,2003,20(2):7-10
[28]杨丽徙,朱向前,陈根永,等.基于Voronoi图的变电站优化规划方法.电力系统及其自动化学报,2006,18(5),10-13
[29]杨丽徒,贾德峰,任群,等.数据融合技术在变电站选址中的应用.电力自动化设备,2003,23(8):57-59
[30]刘自发.基于智能优化算法的配电网络规划与优化运行研究[博士学位论文].天津:天津大学电力系统及其自动化专业,2005
[31]王成山,刘涛,谢莹华.基于混合遗传算法的变电站选址定容.电力系统自动化,2006,30(6),30-34
[32]王成山,魏海洋,肖俊,等.变电站选址定容两阶段优化规划方法.电力系统自动化,2005,29(4):62-66
[33]杨丽徙,王金凤,段嘉平.变电站定位及供电区域划分的计算几何方法.郑州大学学报(工学版),2003,24(4):16-18.10
[34]陈根军,唐国庆.基于禁忌搜索与蚁群最优结合算法的配电网规划.电网技术.2005,29(2):23-28
[35]LIU Zifa,GE Shaoyun,YU Yixin.Optimal Reactive Power Dispatch Using Chaotic Particle Swarm Optimization Algorithm.Automation of Electric Power Systems,2005,29(7):53-57
[36]刘军,刘自发,黄伟等.基于混合微分演化算法的配电网架结构智能规划.电力系统自动化,2007,31(2):32-37
[37]张弘鹏,余贻鑫.基于Agent行为和范例学习的遗传算法在城网规划中的应用.电力系统自动化,2003,27(3):45-49
[38]王天华,王平洋,范明天.用演化算法求解多阶段配电网规划问题.中国电机工程学报,2000,20(3):34-39
[39]余健明,吴海峰,杨文字.基于改进多种群遗传算法的配电网规划.电网技术,2005,29(7):36-61
[40]刘军,张林锋,张建华.基于改进免疫遗传算法的城市电网规划.水电能源科学,2007,25(3):92-95
[41]伍力,吴捷,钟丹虹.多目标优化改进遗传算法在电网规划中的应用.电力系统自动,2000,24(12):45-48
[42]顾洁,陈章潮,包海龙.混合遗传—模拟退火算法在电网规划中的应用.上海交通大学学报,1999,33(4):485-487
[43]E.C.Yeh,Hahn Tram.Information Integration in Computerized Distribution System Planning.IEEE.Transactions on Power System.1997,12(2):142-149
[44]Zarko Sumic.Automated Underground Residential Distribution Design.Part 1:Conceptual Design,IEEE Transaction on Power Delivery,1993,18(2):34-39
[45]Z.Sumic,et al.Automated Underground Residential Retribution Design.Part 2:Prototypeimplementation and Results.IEEE Transaction on Power Delivery,1993,8(2):655-650
[46]吴奇石,邱家驹.基于GIS的配电网规划人工智能方法(一).电力系统自动化,1998,22(10):17-19
[47]吴奇石,邱家驹.基于GIS的配电网规划人工智能方法(二).电力系统自动化,1998,22(11):21-23
[48]唐琳.配电自动化通信系统的设计与实现.电力系统通信,2003,24(12):45-47
[49]朱大萌,陈立伟.配电自动化系统中的通信系统研究.信息技术,2004,28(8):49-51
[50]李惠宇,罗小莉,于盛林.一种基于GPRS的配电自动化系统方案.电力系统自动化,2003,27(24):63-65
[51]胡勇,漆刚,陈麟,杨炜.信息系统风险量化评估指标体系.四川大学学报(自然科学版),2006,43(5):1048-1052
[52]赵冬梅,马建峰,王跃生.信息系统的模糊风险评估模型.通信学报,2007,28(4):51-56
[53]高会生,孙逸群,冉静学.电力光纤保护通道安全风险评估指标的研究.继电器,2007,35(3):61-65
[54]高会生,冉静学,孙逸群.基于改进层析分析法的电力光纤通信网风险评估.华北电力大学学报,2008,35(1):98-101
[55]丛琳,李志民,潘明惠,高昆仑,偏瑞琪.基于模糊综合评判法的电力系统信息安全评估.电力系统自动化,2004,28(12):65-70
[56]李志民,丛琳,郑颖,潘明惠,偏瑞琪.基于SSE-CMM的电力信息安全工程评估.电力系统自动化,2003,27(23):37-40
[57]王伟,李春平,李建彬.信息系统风险评估方法的研究.计算机工程与设计,2007,28(14),PP:3473-3475
[58]Christopher Alberts,Audrey Dorofee.信息安全管理.北京:清华大学出版社,2003
[58]冯登国,张阳,张玉清.信息安全风险评估综述.通信学报,2004,25(7):10-18
[59]李梁,黄新芳,赵霖.威胁树模型在风险评估中的应用.计算机应用,2003,23(12):188-190
[60]Kennedy,J.,Eberhart,R.,Particle Swarm Optimization.Perth,Australia:IEEE International Conference on Neural Networks,1995,4:1942 -1948
[61]Ray T,Liew K.M.,A Swarm with an Effective Infortmation Sharing Mechanism for Unconstrained and Constrained Single Objective Optimization Problems,Seoul:IEEE International Conference on Evolutionary Computation,2001:752-760
[621 Angeline P.J.,Using Selection to Improve Particle Swarm Optimization,Anchorage:IEEE International Conference on Evolutionary Computation,1998:842-849
[63]C.F.Juang.A Hybrid of Genetic Algorithm and Particle Swarm Optimization for Recurrent Network Design,IEEE Trans.on System,Man and Cybernetics,Part B,2004,24(2):997-1006
[64]黄艳新,周春光,邹淑雪,等.一种基于类覆盖和粒子群优化的模糊神经网络系统.计算机研究与发展,2004,41(7):1053-1061
[65]冯林,张名举,贺明峰,等.基于粒子群优化技术的点匹配算法.系统仿真学报,2004,16(8):1686-1691
[66]赵波,郭创新,曹一家.基于粒子群优化算法和动态调整罚函数的最优潮流计算.电工技术学报,2004,19(5):47-54
[67]Iacoban,R.,Reynolds,R.G.,Brewster,J.Modeling the Impact of Culture on Social Interaction and Problem Solving.In:Cultural swarms eds.Proceedings of the 2003IEEE Swarm Intelligence Symposium,2003.205-211
[68]Eberhart R.C.,Shi Y.Particle swarm optimization,developments,applications and resources.Proceedings of the IEEE Congress on Evolutionary Computation,Piscataway,2001.81-86
[69]Shi Yuhui,Eberhart R.Parameter selection in particle swarm optimization.Proceedings of the 7th Annual Conference on Evolutionary Programming.Washington DC:1998.591-600
[70]Eberhart R.,Shi Yuhui,Tracking and optimizing dynamic systems with particle swarms,Proceedings IEEE International Conference on Evolutionary Computation.Hawaii:2001.942-950
[71]徐海,刘石,马勇,等.基于改进粒子群游优化的模糊逻辑系统自学习算法.计算机工程与应用,2000,7(2):62-63
[72]Shi Yuhui,Eberhart R.A modified particle swarm optimizer.Proceedings IEEE International Conference on Evolutionary Computation.Alaska:1998.292-697
[72]Shi Yuhui,Eberhart R.C.Empirical study of particle swarm optimization.Proceeding of Congress on Evolutionary Computation.Piscataway:1999.1945-1949
[73]Clerc M.The swarm and the queen:towards a deterministic and adaptive particle swarm optimization.Proceedings of the Congress on Evolutionary Computation.Piscataway:1999.1951-1957.
[74]Angeline P.Using selection to improve particle swarm optimization.Proceedings of IJCNN.Washington:1999.84-89
[75]Fukuyama Y.Modern Heuristic Optimization Techniques with Applications to Power Systems.Proceedings of IEEE Power Engineering Society,Fundamentals of particle swarm techniques:2002.45-51
[76]Suganthan P.N.,Particle swarm optimizer with neighborhood operator.Proceedings of the Congress on Evolutionary Computation.Piscataway:1999.1958-1961.
[77]Parsopoulos K.E.,Plagianakos V.P,,Magoulas G.D,,et al.Improving particle swarm optimizer by function "stretching",Hadjisavvas N.,Pardalos P.,Advances in Convex Analysis and Global Optimization,The Netherlands:Kluwer Academic Publishers,2001.445-457
[78]金义雄,程浩忠,严健勇,等.改进粒子群算法及其在输电网规划中的应用.中国电机工程学报,2005,25(4),46-50
[79]Storn R.System Design by Constraint Adaptation and Differential Evolution.IEEE Transactions on Evolutionary Computation,1999,3(1):22-34
[80]梁才浩,段献忠,钟志勇.基于差异进化和PC集群的并行无功优化.电力系统自动化,2006,30(1):29-34
[81]冯琦,周德云.基于微分进化算法的时问最优路径规划.计算机工程与应用,2005,12(21):74-75
[82]颜学峰,余娟,钱锋.自适应变异差分进化算法估计软测量参数.控制理论与应用,2006,23(5):744-748
[83]吴亮红,王耀南,袁小芳,等.自适应二次变异差分进化算法.控制与决策,2006,21(8):898-902
[84]D.Zaharie.Control of population diversity and adaptation in differential evolution algorithms,In:R.Matouek,P.Omera eds.Proceedings of Mendel 2003,Ninth International Conference on Soft Computing.Brno:2003.41-46
[85]Bremermann H J.Chemotaxis and Optimization.J.Franklin Inst.,1974,297:397-404
[86]Kennedy J,Eberhart R.Particle Swarm Optimization.Proc.IEEE Int.Conf.on Neural Networks,1995,1942-1948
[87]朱庆保.蚁群优化算法的收敛性分析[J].控制与决策.2006,21(7):763-766
[88]Storn R,Price K.Differential Evolution-a Simple and Efficient Heuristic for Global Optimization over Continuous Spaces.Journal of Global Optimization.Kluwer Academic Publishers,1997,11:341-359
[89]李威武,王慧,邹志君,钱积新.基于细菌群体趋药性的函数优化方法.电路与系统学报,2005,10(1):58-63
[90]黄伟,张建华,张聪,等.基于细菌群体趋药性算法的电力系统无功优化.电力系统自动化,2007,(7):29-33
[91]Sibylle D.Muller,Jarno Marchetto.Optimization Based on Bacterial Chemotaxis.IEEE Transactions on Evolutionary Computation,2002,6(1):16-30
[92]冯琦,周德云.基于微分进化算法的时间最优路径规划.计算机工程与应用,2005,12(21):74-76
[93]Storn R.System Design by Constraint Adaptation and Differential Evolution.IEEE Transactions on Evolutionary Computation,1999,3(1):22-34
[94]周培德.计算几何—算法分析与设计.北京:清华大学出版社,2000
[95]李圣权,胡鹏,闫卫阳.基于加权Voronoi图的城市影响范围划分.武汉大学学报(工学),2004,37(1):94-97
[96]陈军,赵仁亮,乔朝飞.基于Voronoi图的GIS空间分析研究.武汉大学学报,28(5):32-36
[97]Cronin T.Automated Reasoning with Contour Maps.Computers & Geosciences,1995,21(5):609-618
[98]刘建军,王东华,商瑶玲.数字化等高线质量的软件自动检查方法.测绘科学,2000,26(4):36-38
[99]Aumann G,Ebner H,Tang L.Automated Derivation of Skeleton Lines from Digitized Contours.ISPRS Journal of Photogrammetry and Remote Sensing,1991,46:259-268
[100]Gold C,Dakowicz M.Terrain Modelling Based on Contours and Slpoes.Proccessing and Applications.Ottawa:Symposium on Geospatial Theory,2002
[101]Qiao C,Chen J,Li Z,Liu J.Some Rules for Identifying Spatial Relationships of Contours Based on Contour Tree.ISPRS Commission Ⅱ Symposium:Integrated Systems for Spatial Data Production,Custodian and Decision Support,2002
[102]Aurenhammer F,Edelsbrunner H.An Optimal Algorithm for Constructing the Weighted Voronoi Diagram in the Plane.Pattern Recognition,1984,17(2):251-257
[103]Hu Peng,You Lian,Yang Chuan-yong,etc.Cartographic Algebra.Wuhan:Wuhan University Press.2002,152-165,118-119,125-128
[104]Chen Shu-peng,Urbanlization and Urban Geographic Information System.Beijing:Science Press.1999,171-197
[105]Okabe A,Boots B,Sugihara K.nearest Neighborhood Operations with Generalized Voronoi Diagram.International Journal of Geographical Information Systems,1994,8(1):43-51
[106]李成名,陈军.Voronoi图生成的栅格算法.武汉测绘科技大学学报,1998,23(3):208-210
[107]Wu Xiaojun,Luo Xue fang.The Algorithm For Creating Weighted Voronoi Diagrams Based on Cellular Automata.Proceedings of the 6th World Congress on Intelligent Control and Automation.Dalian,China:Intelligent Control and Automation,2006
[108]王林梅,黄民翔.变电站站址两阶段优化规划的实用改进方法.浙江电力,2006,5(3):1-5
[109]杨丽徒,王家耀,贾德峰,等.GIS与模糊模式识别理论在变电站选址中的应用.电力系统自动化,2003,27(18):87-89
[110]刘艳,顾雪平.评估黑启动方案的层次化数据包络分析方法.电力系统自动化,2006,30(21):33-38
[111]戴勇.基于AHP的DEA分析基础上的虚拟物流企业联盟伙伴选择.系统工程,2002,20(3):47-51
[112]Banker R D,Morey R.The Use of Categorical Variables in Data Envelopment Analysis.Management Science,1986,32(12):1613-1626
[113]Cook W D,KressM,SeifordL.On the Use of Ordinal Data in Data Envelopment Analysis.Journal of the Operational Research Society,1993,44(2):133-140
[114]张景义.一类偏好结构下的DEA分析方法和模型:[硕士学位论文].大连:大连理工大学管理学院,1997
[115]刘寅东,李树范,唐焕文.船型技术经济综合评价的DEA方法.大连理工大学学报,1995,(6):873-878
[116]Banker R D,Morey R.The Use of Categorical Variables in Data Envelopment Analysis.Management Science,1986,32(12):1613-1626
[117]Cook W D,KressM,SeifordL.On the Use of Ordinal Data in Data Envelopment Analysis.Journal of the Operational Research Society,1993,44(2):133-140
[118]Chames A,CooperWW,Wei QL.A Semi-infinite Multi-criteria Programming Approach to Data Envelopment Analysis with Infinitely Many Decision Making Units.The University of Texas at Austin,Center for Cybernetic Studies Report CCS 551,1986
[119]马占新,唐焕文.一个综合的DEA模型及其相关性质.系统工程学报,1999,14(4):311-316
[120]欧进萍.模糊分析设计理论及应用.北京:中国建筑工业出版社,1993,96-113
[121]马占新,唐焕文.DEA有效单元的特征及SEA方法.大连理工大学学报,1999,(4):577-582
[122]周泽昆.评价管理效率的一种新方法.系统工程,1986,(4):42-49
[123]Sengupta JK.Dynamic Data Envelopment Analysis.International Journal of Systems Science,1996,27(3):277-284
[124]Sengupta JK.Data Envelopment Analysis for Efficiency Measurement in the Stochastic Case.Computers and Operations Research,1987,14(2):117-129
[125]刘艳,顾雪平.数据包络分析方法的研究进展.电力系统自动化,2006,30(21):33-38
[126]S.Schoenherr.Wireless technologies for distribution automation.In:Proceeding.IEEE Power Eng.Soc.Transmission Distribution Conference,2003,375-378
[127]张学渊,张予倩.通信产品的可靠性指标现状及分析.可靠性论坛与通信,2003,(7):69-75
[128]程建华,靖继鹏.信息安全风险综合评价指标体系构建和评价方法.现代情报,2008,5(5):65-69
[129]Yager R R.On the Dempster-Shafer Framework and New Combination Rules.Information Science,1989,41(2):93-137
[130]童建军.证据理论及其在决策评价中应用研究:[硕士学位论文].合肥:合肥工业大学企业管理专业,2005
[131]Yager R R.On the Dempster-Shafer Framework and New Combination Rules.Information Science,1989,41(2):93-137
[132]孙全,叶秀清,顾伟康.一种新的基于证据理论的合成公式.电子学报,2000,28(8):117-119
[133]Murphy C.K.Combining Belief Functions When Evidence Conflicts.Decision Support Systems,2000,29(1):1-9
[134]邓勇,施文康.一种改进的证据推理组合规则.上海交通大学学报,2003,37(8):1275-1278
[135]刘念,张建华,段斌,刘文霞,张吴.网络环境下变电站自动化通信系统脆弱性评估.电力系统自动化,2008,32(8):28-33
[136]张吉军.模糊层次分析法(FAHP).模糊系统与数学,2000,14(2):80-88
[2]H.L.Willis,H.Tram,M.V.Engel,et al.Optimization Applications to Power Distribution.IEEE Computer Applications in Power,1995,18(4):25-31
[3]王平洋.迎接新世纪的挑战—电力系统的新动向.电网技术,1998,22(11):1-3
[4]周湶.基于GIS的配电网规划智能决策支持系统及其算法的研究:[博士学位论文].重庆:重庆大学电气工程专业,2004
[5]范超,陆融,余建平.配电网规划后评估系统的研究与开发.华东电力,2007,35(12):57-59
[6]汤亚芳,王建民,程浩忠,等.配电网经济性综合评估体系.电网技术,2007,31(2):127-130
[7]牛东晓,曹树华,赵磊,等.电力负荷预测技术.北京:中国电力出版社,1998
[8]黄伟,费维刚.模糊理论在中长期负荷预测中的应用.电力系统及其自动化学报,1999,11(4):25-29
[9]Peng T.M.,Hubele N.F.,Karady G.G.Advancement in the Application of Neural Network for Short-term Forecasting.Transactions on Power System,1992,7(1):250-257
[10]袁明友,肖先勇,杨洪,等.基于灰色理论的供电系统负荷中长期预测模型及其应用.四川大学学报,2003,34(4):121-124
[11]Willis H L.Spatial Electric Load Forecasting.New York:MarcelDekker,Inc,2002
[12]Chow M Y,Tram H.Application of Fuzzy Multi-objective Decision Making in Spatial Load Forecasting.IEEE Transactions on Power System,1997,12(3):1360-1366
[13]Chow M Y,Tram H.Application of Fuzzy Multi-objective Decision Making in Spatial Load Forecasting.IEEE Transactions on Power Systems,1998,13(3):1360-1366
[14]王天华,王平洋,范明天.遗传算法、模糊逻辑和运输模型在配电网空间负荷预测中的应用.电网技术,1999,23(1):24-28
[15]Lei Shaolan,Sun Caixin,Zhou Quan,et al.Application of Fuzzy Rough Set Theory in Spatial Load Forecasting.Power System Technology,2005,29(9):26-30(in Chinese)
[16]Yu Yixin,Zhang Chongjian,Zhang Hongpeng.Small Area Land-use Analysis in Fuzzy Spatial Load Forecasting Part One Principle.Automation of Electric Power Systems,2001,25(7):23-26(in Chinese)
[17]Wu Bei,Ding Ming,Chen Minjiang.Spatial Load Forecasting Based on Fuzzy Reasoning Multi-objective Programming.Power System Technology,2004,28(15):48-52(in Chinese)
[18]Miranda V,Monteiro C.Fuzzy Inference in Spatial Load Forecasting.In:Halifax,Nova Scotia,eds.Proceedings of IEEE Power Engineering Society Winter Meeting Winter.Canada,2000:1063-1068
[19]Cheng Qiyun,Zhang Xiaoxing,Lei Shaolan,et al.Spatial Load Forecasting Method for Distribution Net Based on Rough Set Data Mining Approach.Transaction of China Electrotechnical Society,2005,20(5):98-102(in Chinese)
[20]Lei Shaolan,Sun Caixin,Zhou Lin,et al.Application of Attribute Reduct Method in Spatial Load Forecasting.Journal of Chongqing University,2004,27(3):85-88(in Chinese)
[21]Wu Bin,Chen Zhangchao,Bao Hailong.Spatial Electric Load Forecasting Based on Artificial Neural Networks and Fuzzy Algorithm.Power System Technology,1999,23(11):1-4(in Chinese)
[22]Wu H C,Lu C N.A Data Mining Approach for Spatial Modeling in Small Area Load Forecast.IEEE Transactions on Power System,2002,17(2):516-521
[23]程浩忠,高赐威,马则良.多目标电网规划的一般最优化模型.上海交通大学学报,2004,38(8):1229-1233
[24]葛少云,李慧,刘洪.基于加权Voronoi图的变电站优化规划.电力系统自动化,2007,31(3):29-34
[25]牛卫平,刘自发,张建华,等.基于GIS和微分进化算法的变电站选址定容.电力系统自动化,2007,31(18):82-86
[26]刘自发,张建华.基于改进多组织粒子群体优化算法的配电网络变电站选址定容.中国电机工程报,2007,27(01):107-111
[27]周敏,程浩忠,周中明.优化理论在城市配电网变电站选址中的应用.供用电,2003,20(2):7-10
[28]杨丽徙,朱向前,陈根永,等.基于Voronoi图的变电站优化规划方法.电力系统及其自动化学报,2006,18(5),10-13
[29]杨丽徒,贾德峰,任群,等.数据融合技术在变电站选址中的应用.电力自动化设备,2003,23(8):57-59
[30]刘自发.基于智能优化算法的配电网络规划与优化运行研究[博士学位论文].天津:天津大学电力系统及其自动化专业,2005
[31]王成山,刘涛,谢莹华.基于混合遗传算法的变电站选址定容.电力系统自动化,2006,30(6),30-34
[32]王成山,魏海洋,肖俊,等.变电站选址定容两阶段优化规划方法.电力系统自动化,2005,29(4):62-66
[33]杨丽徙,王金凤,段嘉平.变电站定位及供电区域划分的计算几何方法.郑州大学学报(工学版),2003,24(4):16-18.10
[34]陈根军,唐国庆.基于禁忌搜索与蚁群最优结合算法的配电网规划.电网技术.2005,29(2):23-28
[35]LIU Zifa,GE Shaoyun,YU Yixin.Optimal Reactive Power Dispatch Using Chaotic Particle Swarm Optimization Algorithm.Automation of Electric Power Systems,2005,29(7):53-57
[36]刘军,刘自发,黄伟等.基于混合微分演化算法的配电网架结构智能规划.电力系统自动化,2007,31(2):32-37
[37]张弘鹏,余贻鑫.基于Agent行为和范例学习的遗传算法在城网规划中的应用.电力系统自动化,2003,27(3):45-49
[38]王天华,王平洋,范明天.用演化算法求解多阶段配电网规划问题.中国电机工程学报,2000,20(3):34-39
[39]余健明,吴海峰,杨文字.基于改进多种群遗传算法的配电网规划.电网技术,2005,29(7):36-61
[40]刘军,张林锋,张建华.基于改进免疫遗传算法的城市电网规划.水电能源科学,2007,25(3):92-95
[41]伍力,吴捷,钟丹虹.多目标优化改进遗传算法在电网规划中的应用.电力系统自动,2000,24(12):45-48
[42]顾洁,陈章潮,包海龙.混合遗传—模拟退火算法在电网规划中的应用.上海交通大学学报,1999,33(4):485-487
[43]E.C.Yeh,Hahn Tram.Information Integration in Computerized Distribution System Planning.IEEE.Transactions on Power System.1997,12(2):142-149
[44]Zarko Sumic.Automated Underground Residential Distribution Design.Part 1:Conceptual Design,IEEE Transaction on Power Delivery,1993,18(2):34-39
[45]Z.Sumic,et al.Automated Underground Residential Retribution Design.Part 2:Prototypeimplementation and Results.IEEE Transaction on Power Delivery,1993,8(2):655-650
[46]吴奇石,邱家驹.基于GIS的配电网规划人工智能方法(一).电力系统自动化,1998,22(10):17-19
[47]吴奇石,邱家驹.基于GIS的配电网规划人工智能方法(二).电力系统自动化,1998,22(11):21-23
[48]唐琳.配电自动化通信系统的设计与实现.电力系统通信,2003,24(12):45-47
[49]朱大萌,陈立伟.配电自动化系统中的通信系统研究.信息技术,2004,28(8):49-51
[50]李惠宇,罗小莉,于盛林.一种基于GPRS的配电自动化系统方案.电力系统自动化,2003,27(24):63-65
[51]胡勇,漆刚,陈麟,杨炜.信息系统风险量化评估指标体系.四川大学学报(自然科学版),2006,43(5):1048-1052
[52]赵冬梅,马建峰,王跃生.信息系统的模糊风险评估模型.通信学报,2007,28(4):51-56
[53]高会生,孙逸群,冉静学.电力光纤保护通道安全风险评估指标的研究.继电器,2007,35(3):61-65
[54]高会生,冉静学,孙逸群.基于改进层析分析法的电力光纤通信网风险评估.华北电力大学学报,2008,35(1):98-101
[55]丛琳,李志民,潘明惠,高昆仑,偏瑞琪.基于模糊综合评判法的电力系统信息安全评估.电力系统自动化,2004,28(12):65-70
[56]李志民,丛琳,郑颖,潘明惠,偏瑞琪.基于SSE-CMM的电力信息安全工程评估.电力系统自动化,2003,27(23):37-40
[57]王伟,李春平,李建彬.信息系统风险评估方法的研究.计算机工程与设计,2007,28(14),PP:3473-3475
[58]Christopher Alberts,Audrey Dorofee.信息安全管理.北京:清华大学出版社,2003
[58]冯登国,张阳,张玉清.信息安全风险评估综述.通信学报,2004,25(7):10-18
[59]李梁,黄新芳,赵霖.威胁树模型在风险评估中的应用.计算机应用,2003,23(12):188-190
[60]Kennedy,J.,Eberhart,R.,Particle Swarm Optimization.Perth,Australia:IEEE International Conference on Neural Networks,1995,4:1942 -1948
[61]Ray T,Liew K.M.,A Swarm with an Effective Infortmation Sharing Mechanism for Unconstrained and Constrained Single Objective Optimization Problems,Seoul:IEEE International Conference on Evolutionary Computation,2001:752-760
[621 Angeline P.J.,Using Selection to Improve Particle Swarm Optimization,Anchorage:IEEE International Conference on Evolutionary Computation,1998:842-849
[63]C.F.Juang.A Hybrid of Genetic Algorithm and Particle Swarm Optimization for Recurrent Network Design,IEEE Trans.on System,Man and Cybernetics,Part B,2004,24(2):997-1006
[64]黄艳新,周春光,邹淑雪,等.一种基于类覆盖和粒子群优化的模糊神经网络系统.计算机研究与发展,2004,41(7):1053-1061
[65]冯林,张名举,贺明峰,等.基于粒子群优化技术的点匹配算法.系统仿真学报,2004,16(8):1686-1691
[66]赵波,郭创新,曹一家.基于粒子群优化算法和动态调整罚函数的最优潮流计算.电工技术学报,2004,19(5):47-54
[67]Iacoban,R.,Reynolds,R.G.,Brewster,J.Modeling the Impact of Culture on Social Interaction and Problem Solving.In:Cultural swarms eds.Proceedings of the 2003IEEE Swarm Intelligence Symposium,2003.205-211
[68]Eberhart R.C.,Shi Y.Particle swarm optimization,developments,applications and resources.Proceedings of the IEEE Congress on Evolutionary Computation,Piscataway,2001.81-86
[69]Shi Yuhui,Eberhart R.Parameter selection in particle swarm optimization.Proceedings of the 7th Annual Conference on Evolutionary Programming.Washington DC:1998.591-600
[70]Eberhart R.,Shi Yuhui,Tracking and optimizing dynamic systems with particle swarms,Proceedings IEEE International Conference on Evolutionary Computation.Hawaii:2001.942-950
[71]徐海,刘石,马勇,等.基于改进粒子群游优化的模糊逻辑系统自学习算法.计算机工程与应用,2000,7(2):62-63
[72]Shi Yuhui,Eberhart R.A modified particle swarm optimizer.Proceedings IEEE International Conference on Evolutionary Computation.Alaska:1998.292-697
[72]Shi Yuhui,Eberhart R.C.Empirical study of particle swarm optimization.Proceeding of Congress on Evolutionary Computation.Piscataway:1999.1945-1949
[73]Clerc M.The swarm and the queen:towards a deterministic and adaptive particle swarm optimization.Proceedings of the Congress on Evolutionary Computation.Piscataway:1999.1951-1957.
[74]Angeline P.Using selection to improve particle swarm optimization.Proceedings of IJCNN.Washington:1999.84-89
[75]Fukuyama Y.Modern Heuristic Optimization Techniques with Applications to Power Systems.Proceedings of IEEE Power Engineering Society,Fundamentals of particle swarm techniques:2002.45-51
[76]Suganthan P.N.,Particle swarm optimizer with neighborhood operator.Proceedings of the Congress on Evolutionary Computation.Piscataway:1999.1958-1961.
[77]Parsopoulos K.E.,Plagianakos V.P,,Magoulas G.D,,et al.Improving particle swarm optimizer by function "stretching",Hadjisavvas N.,Pardalos P.,Advances in Convex Analysis and Global Optimization,The Netherlands:Kluwer Academic Publishers,2001.445-457
[78]金义雄,程浩忠,严健勇,等.改进粒子群算法及其在输电网规划中的应用.中国电机工程学报,2005,25(4),46-50
[79]Storn R.System Design by Constraint Adaptation and Differential Evolution.IEEE Transactions on Evolutionary Computation,1999,3(1):22-34
[80]梁才浩,段献忠,钟志勇.基于差异进化和PC集群的并行无功优化.电力系统自动化,2006,30(1):29-34
[81]冯琦,周德云.基于微分进化算法的时问最优路径规划.计算机工程与应用,2005,12(21):74-75
[82]颜学峰,余娟,钱锋.自适应变异差分进化算法估计软测量参数.控制理论与应用,2006,23(5):744-748
[83]吴亮红,王耀南,袁小芳,等.自适应二次变异差分进化算法.控制与决策,2006,21(8):898-902
[84]D.Zaharie.Control of population diversity and adaptation in differential evolution algorithms,In:R.Matouek,P.Omera eds.Proceedings of Mendel 2003,Ninth International Conference on Soft Computing.Brno:2003.41-46
[85]Bremermann H J.Chemotaxis and Optimization.J.Franklin Inst.,1974,297:397-404
[86]Kennedy J,Eberhart R.Particle Swarm Optimization.Proc.IEEE Int.Conf.on Neural Networks,1995,1942-1948
[87]朱庆保.蚁群优化算法的收敛性分析[J].控制与决策.2006,21(7):763-766
[88]Storn R,Price K.Differential Evolution-a Simple and Efficient Heuristic for Global Optimization over Continuous Spaces.Journal of Global Optimization.Kluwer Academic Publishers,1997,11:341-359
[89]李威武,王慧,邹志君,钱积新.基于细菌群体趋药性的函数优化方法.电路与系统学报,2005,10(1):58-63
[90]黄伟,张建华,张聪,等.基于细菌群体趋药性算法的电力系统无功优化.电力系统自动化,2007,(7):29-33
[91]Sibylle D.Muller,Jarno Marchetto.Optimization Based on Bacterial Chemotaxis.IEEE Transactions on Evolutionary Computation,2002,6(1):16-30
[92]冯琦,周德云.基于微分进化算法的时间最优路径规划.计算机工程与应用,2005,12(21):74-76
[93]Storn R.System Design by Constraint Adaptation and Differential Evolution.IEEE Transactions on Evolutionary Computation,1999,3(1):22-34
[94]周培德.计算几何—算法分析与设计.北京:清华大学出版社,2000
[95]李圣权,胡鹏,闫卫阳.基于加权Voronoi图的城市影响范围划分.武汉大学学报(工学),2004,37(1):94-97
[96]陈军,赵仁亮,乔朝飞.基于Voronoi图的GIS空间分析研究.武汉大学学报,28(5):32-36
[97]Cronin T.Automated Reasoning with Contour Maps.Computers & Geosciences,1995,21(5):609-618
[98]刘建军,王东华,商瑶玲.数字化等高线质量的软件自动检查方法.测绘科学,2000,26(4):36-38
[99]Aumann G,Ebner H,Tang L.Automated Derivation of Skeleton Lines from Digitized Contours.ISPRS Journal of Photogrammetry and Remote Sensing,1991,46:259-268
[100]Gold C,Dakowicz M.Terrain Modelling Based on Contours and Slpoes.Proccessing and Applications.Ottawa:Symposium on Geospatial Theory,2002
[101]Qiao C,Chen J,Li Z,Liu J.Some Rules for Identifying Spatial Relationships of Contours Based on Contour Tree.ISPRS Commission Ⅱ Symposium:Integrated Systems for Spatial Data Production,Custodian and Decision Support,2002
[102]Aurenhammer F,Edelsbrunner H.An Optimal Algorithm for Constructing the Weighted Voronoi Diagram in the Plane.Pattern Recognition,1984,17(2):251-257
[103]Hu Peng,You Lian,Yang Chuan-yong,etc.Cartographic Algebra.Wuhan:Wuhan University Press.2002,152-165,118-119,125-128
[104]Chen Shu-peng,Urbanlization and Urban Geographic Information System.Beijing:Science Press.1999,171-197
[105]Okabe A,Boots B,Sugihara K.nearest Neighborhood Operations with Generalized Voronoi Diagram.International Journal of Geographical Information Systems,1994,8(1):43-51
[106]李成名,陈军.Voronoi图生成的栅格算法.武汉测绘科技大学学报,1998,23(3):208-210
[107]Wu Xiaojun,Luo Xue fang.The Algorithm For Creating Weighted Voronoi Diagrams Based on Cellular Automata.Proceedings of the 6th World Congress on Intelligent Control and Automation.Dalian,China:Intelligent Control and Automation,2006
[108]王林梅,黄民翔.变电站站址两阶段优化规划的实用改进方法.浙江电力,2006,5(3):1-5
[109]杨丽徒,王家耀,贾德峰,等.GIS与模糊模式识别理论在变电站选址中的应用.电力系统自动化,2003,27(18):87-89
[110]刘艳,顾雪平.评估黑启动方案的层次化数据包络分析方法.电力系统自动化,2006,30(21):33-38
[111]戴勇.基于AHP的DEA分析基础上的虚拟物流企业联盟伙伴选择.系统工程,2002,20(3):47-51
[112]Banker R D,Morey R.The Use of Categorical Variables in Data Envelopment Analysis.Management Science,1986,32(12):1613-1626
[113]Cook W D,KressM,SeifordL.On the Use of Ordinal Data in Data Envelopment Analysis.Journal of the Operational Research Society,1993,44(2):133-140
[114]张景义.一类偏好结构下的DEA分析方法和模型:[硕士学位论文].大连:大连理工大学管理学院,1997
[115]刘寅东,李树范,唐焕文.船型技术经济综合评价的DEA方法.大连理工大学学报,1995,(6):873-878
[116]Banker R D,Morey R.The Use of Categorical Variables in Data Envelopment Analysis.Management Science,1986,32(12):1613-1626
[117]Cook W D,KressM,SeifordL.On the Use of Ordinal Data in Data Envelopment Analysis.Journal of the Operational Research Society,1993,44(2):133-140
[118]Chames A,CooperWW,Wei QL.A Semi-infinite Multi-criteria Programming Approach to Data Envelopment Analysis with Infinitely Many Decision Making Units.The University of Texas at Austin,Center for Cybernetic Studies Report CCS 551,1986
[119]马占新,唐焕文.一个综合的DEA模型及其相关性质.系统工程学报,1999,14(4):311-316
[120]欧进萍.模糊分析设计理论及应用.北京:中国建筑工业出版社,1993,96-113
[121]马占新,唐焕文.DEA有效单元的特征及SEA方法.大连理工大学学报,1999,(4):577-582
[122]周泽昆.评价管理效率的一种新方法.系统工程,1986,(4):42-49
[123]Sengupta JK.Dynamic Data Envelopment Analysis.International Journal of Systems Science,1996,27(3):277-284
[124]Sengupta JK.Data Envelopment Analysis for Efficiency Measurement in the Stochastic Case.Computers and Operations Research,1987,14(2):117-129
[125]刘艳,顾雪平.数据包络分析方法的研究进展.电力系统自动化,2006,30(21):33-38
[126]S.Schoenherr.Wireless technologies for distribution automation.In:Proceeding.IEEE Power Eng.Soc.Transmission Distribution Conference,2003,375-378
[127]张学渊,张予倩.通信产品的可靠性指标现状及分析.可靠性论坛与通信,2003,(7):69-75
[128]程建华,靖继鹏.信息安全风险综合评价指标体系构建和评价方法.现代情报,2008,5(5):65-69
[129]Yager R R.On the Dempster-Shafer Framework and New Combination Rules.Information Science,1989,41(2):93-137
[130]童建军.证据理论及其在决策评价中应用研究:[硕士学位论文].合肥:合肥工业大学企业管理专业,2005
[131]Yager R R.On the Dempster-Shafer Framework and New Combination Rules.Information Science,1989,41(2):93-137
[132]孙全,叶秀清,顾伟康.一种新的基于证据理论的合成公式.电子学报,2000,28(8):117-119
[133]Murphy C.K.Combining Belief Functions When Evidence Conflicts.Decision Support Systems,2000,29(1):1-9
[134]邓勇,施文康.一种改进的证据推理组合规则.上海交通大学学报,2003,37(8):1275-1278
[135]刘念,张建华,段斌,刘文霞,张吴.网络环境下变电站自动化通信系统脆弱性评估.电力系统自动化,2008,32(8):28-33
[136]张吉军.模糊层次分析法(FAHP).模糊系统与数学,2000,14(2):80-88