火电工程项目绿色和谐建设的后评价研究
|
摘要
发电项目具有技术密集和资金密集的属性,建设一个火力发电厂需要耗费大量的财力、人力和物力。项目一旦建成就要持续数十年的运营期,即使客观环境和自身状况发生较大变化亦无法实施转产。因此,电力项目不仅存在着建设期风险,更由于外部条件的不断变化而存在着较大的经营期风险,能否建成一个与时代要求相适应的发电项目是政府管理部门和各投资主体实施有效管理和决策的关键。开展火电建设项目绿色和谐后评价,既是投资方和政府相关部门的迫切愿望,更为今后的项目开发、投资、建设决策及管理积累经验,并为指导投资方向提供理论依据。
提出了绿色和谐后评价概念。结合中国电力市场改革特点和宏观经济环境,对中国火电项目绿色和谐后评价背景和意义进行阐述。结合相关的火电厂后评价准则和现有火电厂工程项目的研究成果,分析绿色和谐建设对于火电工程项目后评价的意义,提出建立火电工程项目绿色和谐建设后评价指标体系的基本原则和思路。
提出了绿色和谐后评价指标体系。普通火电工程项目的综合评价,不能反映火电工程给社会带来的绿色和谐效益。本文通过从节能降耗、资源综合利用、控制污染物排放等角度,构建了绿色评价指标体系;通过项目内部的和谐――人与人的和谐、人与设备的和谐、人与环境的和谐、劳资关系的和谐、项目自身经济性的和谐,以及项目与外部的和谐――项目与社会的和谐、项目与自然环境的和谐、项目与经济环境的和谐以及项目与市场环境的和谐等角度建立和谐评价指标体系。
提出了基于“功能驱动”和“差异驱动”分层递阶模糊综合评价模型。特征值法和熵权法是两种分别基于“功能驱动”和“差异驱动”的权重确定方法,“递阶模型”与“模糊综合评价”经过有效结合,本文构建了基于“功能驱动”和“差异驱动”组合权分层递阶模糊综合评价模型,评价结果显示评价方法适应本文提出的评价系统,结合了主观定权和客观定权的优点不仅具有公开透明性,还在一定的程度上保证了继承性。
提出了基于隐马尔科夫预测模型和时间序列乘法模型的优选组合预测模型,并用来对后评价指标体系中需要预测的指标进行预测,得到了满意的预测效果。
以河南三门峡电厂2×600MW火电项目为案例,进行绿色和谐综合评价,并针对评价结果,说明成效,分析问题,分别对绿色和谐各个方面提出针对性建议,以作参考和被更广泛的借鉴。
As power projects are both technology-intensive and capital-intensive, the construction of a thermal power plant requires massive financial, human and material resources. Once completed, they have to keep on operation for decades and will not be able to transfer to other businesses even if significant changes occurred in the objective environment and its own state. As a result, power projects are not only put at risk during construction period, they are also largely exposed to risks during operation period due to constant changes of external conditions. Whether a power project adapted to the demands of times can be built up is the key to effective management and decision-making for government administration departments and various investment subjects. It is the urgent desire of both investors and relevant government institutions to carry out green and harmonious post-assessment for thermal power project, which furthermore gathers experience for future project development, investment, construction decision-making and management and even provides theoretical basis for guiding investment orientation.
The concept of green and harmonious post-assessment concept is put forward. Combing the characteristics of power market reform and macroeconomic environment in China, this paper elaborates the background and significance of green and harmonious post-assessment for thermal power project in China. Investigating relevant thermal power plant post-assessment criteria as well as currently available research findings of thermal power projects, the significance of green and harmonious construction to thermal power project post-assessment is analyzed and the basic principles and ideas for establishing green and harmonious post-assessment index system of thermal power project construction is advanced.
The index system of green and harmonious assessment is brought up. The ordinary comprehensive assessment for thermal power projects can not reflect the green and harmonious benefits the thermal power project brought to the community. This paper builds the green index system from the aspects of energy saving, comprehensive utilization of resources and pollutant control and etc.; it builds the harmonious assessment index system through the angles of internal harmony of project, namely harmony between human, harmony between human and equipment, harmony between human and environment, harmony between labor and management, harmony of project intrinsic economic efficiency, as well as harmony between project and external surroundings, namely harmony between project and society, harmony between project and natural environment, harmony between project and economic environment and harmony between project and market environment.
This paper proposed a hierarchical fuzzy comprehensive assessment model based on "feature-driven" and "difference-driven" combined weight. Eigenvalue method and entropy weight method are based on "feature-driven" and "difference-driven" approach respectively to determine the weights. With a structure design of "hierarchical model" and "fuzzy comprehensive assessment", this paper constructs a hierarchical fuzzy comprehensive assessment model based on the "Function Driver" and "difference-driven" combination weights. The assessment results shows that this assessment method adapts to the assessment system proposed in this paper, which combines the advantages of both subjective weight and objective weight, thus possessing an open and transparent nature and to a certain extent, ensures the inheritability.
The preferred combination forecasting model based on hidden Markov models and time series multiplicative is proposed in this paper, which is adopted to forecast indicators in need of prediction in post-assessment system and satisfactory forecasting results are attained.
The 2×600MW thermal power project in Sanmenxia, Henan, China is taken as a case for green and harmonious comprehensive assessment. Based on the assessment result, effectiveness is shown, problems are analyzed and suggestions are put forward concerning various aspects of green and harmony for more extensive reference.
提出了绿色和谐后评价概念。结合中国电力市场改革特点和宏观经济环境,对中国火电项目绿色和谐后评价背景和意义进行阐述。结合相关的火电厂后评价准则和现有火电厂工程项目的研究成果,分析绿色和谐建设对于火电工程项目后评价的意义,提出建立火电工程项目绿色和谐建设后评价指标体系的基本原则和思路。
提出了绿色和谐后评价指标体系。普通火电工程项目的综合评价,不能反映火电工程给社会带来的绿色和谐效益。本文通过从节能降耗、资源综合利用、控制污染物排放等角度,构建了绿色评价指标体系;通过项目内部的和谐――人与人的和谐、人与设备的和谐、人与环境的和谐、劳资关系的和谐、项目自身经济性的和谐,以及项目与外部的和谐――项目与社会的和谐、项目与自然环境的和谐、项目与经济环境的和谐以及项目与市场环境的和谐等角度建立和谐评价指标体系。
提出了基于“功能驱动”和“差异驱动”分层递阶模糊综合评价模型。特征值法和熵权法是两种分别基于“功能驱动”和“差异驱动”的权重确定方法,“递阶模型”与“模糊综合评价”经过有效结合,本文构建了基于“功能驱动”和“差异驱动”组合权分层递阶模糊综合评价模型,评价结果显示评价方法适应本文提出的评价系统,结合了主观定权和客观定权的优点不仅具有公开透明性,还在一定的程度上保证了继承性。
提出了基于隐马尔科夫预测模型和时间序列乘法模型的优选组合预测模型,并用来对后评价指标体系中需要预测的指标进行预测,得到了满意的预测效果。
以河南三门峡电厂2×600MW火电项目为案例,进行绿色和谐综合评价,并针对评价结果,说明成效,分析问题,分别对绿色和谐各个方面提出针对性建议,以作参考和被更广泛的借鉴。
As power projects are both technology-intensive and capital-intensive, the construction of a thermal power plant requires massive financial, human and material resources. Once completed, they have to keep on operation for decades and will not be able to transfer to other businesses even if significant changes occurred in the objective environment and its own state. As a result, power projects are not only put at risk during construction period, they are also largely exposed to risks during operation period due to constant changes of external conditions. Whether a power project adapted to the demands of times can be built up is the key to effective management and decision-making for government administration departments and various investment subjects. It is the urgent desire of both investors and relevant government institutions to carry out green and harmonious post-assessment for thermal power project, which furthermore gathers experience for future project development, investment, construction decision-making and management and even provides theoretical basis for guiding investment orientation.
The concept of green and harmonious post-assessment concept is put forward. Combing the characteristics of power market reform and macroeconomic environment in China, this paper elaborates the background and significance of green and harmonious post-assessment for thermal power project in China. Investigating relevant thermal power plant post-assessment criteria as well as currently available research findings of thermal power projects, the significance of green and harmonious construction to thermal power project post-assessment is analyzed and the basic principles and ideas for establishing green and harmonious post-assessment index system of thermal power project construction is advanced.
The index system of green and harmonious assessment is brought up. The ordinary comprehensive assessment for thermal power projects can not reflect the green and harmonious benefits the thermal power project brought to the community. This paper builds the green index system from the aspects of energy saving, comprehensive utilization of resources and pollutant control and etc.; it builds the harmonious assessment index system through the angles of internal harmony of project, namely harmony between human, harmony between human and equipment, harmony between human and environment, harmony between labor and management, harmony of project intrinsic economic efficiency, as well as harmony between project and external surroundings, namely harmony between project and society, harmony between project and natural environment, harmony between project and economic environment and harmony between project and market environment.
This paper proposed a hierarchical fuzzy comprehensive assessment model based on "feature-driven" and "difference-driven" combined weight. Eigenvalue method and entropy weight method are based on "feature-driven" and "difference-driven" approach respectively to determine the weights. With a structure design of "hierarchical model" and "fuzzy comprehensive assessment", this paper constructs a hierarchical fuzzy comprehensive assessment model based on the "Function Driver" and "difference-driven" combination weights. The assessment results shows that this assessment method adapts to the assessment system proposed in this paper, which combines the advantages of both subjective weight and objective weight, thus possessing an open and transparent nature and to a certain extent, ensures the inheritability.
The preferred combination forecasting model based on hidden Markov models and time series multiplicative is proposed in this paper, which is adopted to forecast indicators in need of prediction in post-assessment system and satisfactory forecasting results are attained.
The 2×600MW thermal power project in Sanmenxia, Henan, China is taken as a case for green and harmonious comprehensive assessment. Based on the assessment result, effectiveness is shown, problems are analyzed and suggestions are put forward concerning various aspects of green and harmony for more extensive reference.
引文
[1] Carr V, Tah J H. A fuzzy approach to construction project risk assessment and analysis: construction project risk management system[J]. Advances in Engineering Software. 2001, 32(10-11): 847-857.
[2] Yang J B, Peng S C. Development of a customer satisfaction evaluation model for construction project management[J]. Building and Environment. 2008, 43(4): 458-468.
[3] Imoto S, Yabuuchi Y, Watada J. Fuzzy regression model of R&D project evaluation[J]. Applied Soft Computing. 2008, 8(3): 1266-1273.
[4] Hwang H S, Yu J C. R&D project evaluation model based on fuzzy set priority[J]. Computers & Industrial Engineering. 1998, 35(3-4): 567-570.
[5]柴中华.电力项目后评价理论、方法及应用研究[D].河海大学, 2007.
[6]辛侨.建设项目后评价研究[D].广东工业大学, 2007.
[7]郎启贵.建设项目可持续性后评价指标体系和方法研究[D].重庆大学, 2006.
[8]蔡成果.项目社会经济效益与影响后评价[D].湖南大学, 2001.
[9]唐镇.农网改造项目后评价理论方法及应用研究[D].华北电力大学(北京), 2003.
[10]杨永东.水电工程项目后评价方法研究[D].华北电力大学(北京), 2003.
[11]曲炜.水利工程项目后评价理论探讨[D].河海大学, 2001.
[12]张宝娟.水利工程项目后评价研究[D].沈阳工业大学, 2006.
[13]韩勇.水利建设项目后评价中的社会评价研究[D].天津大学, 2004.
[14]汪辉德.中小型水利水电工程项目施工后评价探索[D].四川大学, 2005.
[15]王育红.路桥投资项目综合后评价及其应用[D].南京航空航天大学, 2006.
[16]邢妍.完善我国政府投资项目后评价体系的研究[D].北京交通大学, 2007.
[17]吕蓬.大型火电厂项目选址的综合分析与研究[D].华北电力大学, 2002.
[18]谷志红.大唐耒阳发电厂建设项目生产及财务后评价研究[D].华北电力大学(河北), 2006.
[19]赵晓坤.耒阳电厂建设项目影响后评价研究[D].华北电力大学(河北), 2006.
[20]王永利.海勃湾电厂三期工程项目建设实施过程后评价研究[D].华北电力大学(河北), 2007.
[21]黄浩,姜学文,霍红刚.变电建设项目模糊综合评价体系设计的研究[J].湖北电力. 2007, 31(2): 68-70.
[22]凌云鹏.海勃湾电厂三期工程项目经济效益后评价研究[D].华北电力大学(河北), 2007.
[23]李嘉荣.西部城市化投资效率的绿色评价指标体系[J].西南农业大学学报(社会科学版). 2007(02).
[24]程俊军,刘心报,虞孝感, et al.工业园区绿色化若干问题的研究[J].预测. 2006(02).
[25]邓朗妮,黄如寤.基于价值工程的绿色施工方案评价[J].施工技术. 2007(S1).
[26]乔昆,支海波,苏青, et al.绿色项目管理的评价体系研究[J].科技导报. 2005(08).
[27]支海波,乔昆,苏青.关于绿色项目管理评价框架的研究[J].科技导报. 2004(11).
[28]尚金成,张立庆.电力节能减排与资源优化配置技术的研究与应用[J].电网技术. 2007(22).
[29]付强,曾国平,王可俐.特大型工程多项目和谐管理绩效评价体系的构建——以大型国企为例[J].建筑经济. 2007(10).
[30]胡永铨.基于和谐发展观的项目社会评价体系研究[J].科技进步与对策. 2006(01).
[31] Sinuany-stern Z, Amitai A. The post-evaluation of an engineering project via AHP[C]. 1991.
[32] Branley B, Fradin R, Kimbrough S O, et al. On heuristic mapping of decision surfaces for post-evaluation analysis[C]. 1997.
[33] Castro R, Ferreira L. A Comparison Between Chronological and Probabilistic Methods to Estimate Wind Power Capacity Credit[J]. Power Engineering Review, IEEE. 2001, 21(10): 62-62.
[34] Castro R M, Ferreira L A. A comparison between chronological and probabilistic methods to estimate wind power capacity credit[J]. Power Systems, IEEE Transactions on Power Systems. 2001, 16(4): 904-909.
[35] Danech-pajouh M, Sauvadet V. A statistical consistency method for evaluating the output from traffic simulation and forecasting models[C]. 2003.
[36] Eid A, Farag A. A Unified Framework for Performance Evaluation of 3-D Reconstruction Techniques[C]. 2004.
[37] Xuewen T, Sifeng L, Zhigeng F, et al. Research of Rrogram Process Time Post-evaluation Grey Critical Path Algorithm Method Based on Grey Data Advantage Relationship[C]. 2006.
[38] Omori Y, Ito K, Nishida S, et al. Study on Supporting Group Discussions by Improving Discussion Skills with Ex Post Evaluation[C]. 2006.
[39] Yongju C, Changho L, Choonseong L, et al. Development of Evaluation System for Management of Collaborative Information System in Mould Company[C]. 2007.
[40] Yi X, Dongguo S, Yunqing W. Ex-post evaluation analysis of flood control engineering system based on grey relation projection method[C]. 2007.
[41] Burget L, Matejka P, Schwarz P, et al. Analysis of Feature Extraction and Channel Compensation in a GMM Speaker Recognition System[J]. Audio, Speech, and Language Processing, IEEE Transactions on Audio, Speech, and Language Processing. 2007, 15(7): 1979-1986.
[42] Xiao Y, Shao D, Wu Y. The Methodology of Post-Evaluation of River Basin Harnessing Project for Sustainable Development Based on Entropy Theory[C]. 2007.
[43] Song P, Yang Q, Feng B. Application of Entropy Coefficient Optimization Model of Multi-Criteria Decision in Post-Evaluation of Urban Rail Transit[C]. 2007.
[44] Zeng S, Tian M, Li J, et al. Post Evaluation of Water Pollution Control Planning for Huai River Basin in China[C]. 2008.
[45]李泽红,刘利,许淑景.熵权评价法在项目投资决策中的运用[J].会计之友(下). 2007(03).
[46]张朝勇,王卓甫.基于熵权的Fuzzy—AHP法的水电工程投标风险决策[J].水利水电技术. 2007(06).
[47]郭庆军,赛云秀.基于熵权决策的项目方案评价[J].统计与决策. 2007(11).
[48]谢武.基于熵的投影决策法在小水电项目方案择优中的应用[J].东北水利水电. 2005(11).
[49]周书敬,宋喜民.熵权方法在房地产投资环境优序评价中的应用[J].基建优化. 2003(02).
[50]周国良.基于熵的不确定性项目投资决策优化模型[J].重庆大学学报(自然科学版). 2003(11).
[51] Tao Y, Xinmiao Y. Fuzzy comprehensive assessment, fuzzy clustering analysis and its application for urban traffic environment quality evaluation[J]. Transportation Research Part D: Transport and Environment. 1998, 3(1): 51-57.
[52]徐靓,张九根,梁雪春.基于熵权决策法的建筑工程项目投标[J].建筑经济. 2006(S1).
[53]熊光蔚.信息熵在建设工程评标中的应用[J].南昌大学学报(工科版). 2007(04).
[54]杨海云,李珍照,常晓林.水电工程项目评标中的熵权决策法及其应用[J].武汉大学学报(工学版). 2005(02).
[55]易明,周国华,张洁.基于熵权的铁路建设多项目优先级评价[J].铁道运输与经济. 2007(10).
[56] Liang Z, Yang K, Sun Y, et al. Decision support for choice optimal power generation projects: Fuzzy comprehensive evaluation model based on the electricity market[J]. Energy Policy. 2006, 34(17): 3359-3364.
[57]马荣国,刘艳妮.公路建设项目综合评价权重确定方法[J].交通运输工程学报. 2005(02).
[58]陈军飞.应用灰色系统评价方法对港口开发项目综合评价[J].水运工程. 2003(01).
[59]陈雷,王延章.基于熵权系数与TOPSIS集成评价决策方法的研究[J].控制与决策. 2003(04).
[60]王梅,王恒栋,周之豪.信息论与水利建设项目的灰色系统评价[J].河海大学学报(自然科学版). 1997(05).
[61]杨建斌,张慧.大型水利项目风险模糊层次综合评价方法研究[J].人民长江. 2007, 38(6): 148-150.
[62]苏平,马维珍,田元福.模糊综合评价法在项目风险管理中的应用[J].兰州交通大学学报. 2005, 24(6): 53-55.
[63]劳本信,刘宁杰,何庆光.基于模糊风险综合评价法的ERP项目风险评价[J].广西财经学院学报. 2006, 19(4): 72-75.
[64]张星,孙建平,李胜. BOT项目风险的模糊综合评价[J].上海经济研究. 2004: 69-73.
[65]张慧,杨建斌.水利投资项目多目标模糊综合评价方法应用探析[J].长江科学院院报. 2006, 23(5): 52-55.
[66]邹永诚,杨艳群.市政交通项目建设次序的模糊综合评价方法[J].石家庄铁道学院学报. 2003, 16(1): 87-90.
[67]陈岩,付贵,刘铭嘉.公路工程项目风险的模糊综合评价[J].北方交通. 2006: 79-80.
[68]李煜华,郎宏文.高新技术项目投资风险的模糊综合评价模型[J].哈尔滨理工大学学报. 2004, 9(1): 72-75.
[69]李聃菱,李静.房地产项目投资环境模糊综合评价[J].山东建筑工程学院学报. 2004, 19(1): 27-31.
[70]赵旭. AHP与模糊综合评价相结合的商业房地产项目融资风险评价[J].基建优化. 2005, 26(6): 69-71.
[71]周高平,周直,陈远祥.基础设施项目投资风险模糊综合评价模型[J].重庆交通学院学报. 2005, 24(1): 107-111.
[72]杨道箭,齐二石. ERP项目成功度评价体系研究[J].工业工程. 2006(04).
[73]吕滨.贷款项目成功度模糊综合评价法探讨[J].中央财经大学学报. 2000(07).
[74]王兆弘,吕薇,刘建伟.成功度法在产能建设项目后评价中的应用[J].油气田地面工程. 2007(07).
[75]张慧颖.基于灰色变权聚类的公路建设项目成功度评价[J].公路. 2006(08).
[76]陈辉,李军. ANN技术评价技改项目成功度的尝试[J].五邑大学学报(自然科学版). 2003(01).
[77]陈章潮.用时间序列预测电力系统负荷.电力系统自动化,1982,4(6):9~13.
[78]赵宏伟,任震,黄雯莹.基于周期自回归模型的短期负荷预测.中国电机工程学报, 1997,17(5):348~351.
[79]吴宏晓,候志俭.基于免疫支持向量机的电力系统短期负荷预测.电网技术,2004,28(23):47~51.
[80]电网短期负荷预测中的应用.电力系统自动化,2001,25,(l7):32~35,52.
[81]谢宏,陈志业.基于小波分解与气象因素影响的电力系统日负荷预测模型研究.中国电机工程学报,2001,10(5):5~10.
[82]刘颖,田彦芬.保定电网最大负荷及用电量的灰色预测.华北电力技术,1995,6(2):25
[83]张昊,郁滨,吴捷.在预测领域中应用模糊控制的研究.自动化学报, 1999(05).
[84] Niu Dongxiao, Kou Bingen, Chu Ye. The combination forecasting model for power load based on evidential theory. WISM’09-AICI’09, 2009:402-405
[85]张庆宝.基于粗糙集属性约简算法和支持向量机的短期负荷预测.电网技术, 2006(08).
[86]郑永康,陈维荣,戴朝华.小波支持向量机与相空间重构结合的短期负荷预测研究.继电器, 2008(07).
[87]祝志慧,孙云莲,季宇.基于经验模式分解和最小二乘支持向量机的短期负荷预测.继电器, 2007(08).
[88]袁小芳,王耀南.基于混沌优化算法的支持向量机参数选取方法.控制与决策, 2006(01).
[89] Hippert HS, Pedreira CE, Castro R,“Neural networks for short-term load forecasting: a review and evaluation,”IEEE Trans Power Sys, Vol. 16, No. 1, pp.44–55, 2001.
[90] Chen B-J, Chang M-W, Lin C-J,“Load forecasting using support vector machines: a study on EUNITE competition,”IEEE Trans Power Syst, Vol. 19, pp.1821–1830, 2001.
[91] Fan S, Chen L.,“Short-term load forecasting based on an adaptive hybrid method”, IEEE Trans Power Syst, Vol.21, No. 1, pp.392–401, 2006..
[92] Schmtlein K. R.,“Combining Forecasts: Operational Adjustments to Theoretically Optimal rules,”Management Science, Vol. 36, No. 4, pp. 1044-1056, Mar. 1990.
[93] Ji Pei-rong, Zhang Yu-weng, Zhao qing,“Application of Combination Forecast Method to Electric Load Forecasting for Power System,”J of China Three Gorges Univ. (Natural Sciences), Vol. 27, No. 8, pp. 398-400, May.2005.
[94] Wang Ji-quan, Zhao Yu-lin,“Application of Combination Forecasting Method in Power Load Forecast,”Electric Power Automation Equipment, Vol. 24, No. 3, pp. 92-94, Jun. 2004.
[95] Li Lin-chuan, Lv Dong, Wu Wen-jie,“A Linear Combination Based Simplified Load Forecasting Method for Power System,”Power System Technology, Vol. 26, No. 2, pp. 10-13, Dec. 2002.
[96] Ma Yong-kai, Tang Xiao-wo,“Research on the Problem of Optimizing Linear Combination Forecasting Model,”Systems Engineering Theory & Practice, Vol. 9, No. 11, pp. 110-123, Nov. 1998.
[97] Xie Kai-gui, Li Chun-yan , Zhou Jia-qi,“Research of the Combination Forecasting Method for Load Based on Artificial Neural Network,”Proceeding of the CSEE, Vol. 22, No. 4, pp. 85-89, Mar. 2002.
[98] Zhao Hai-qing,“The Application to Power Load Forecasting of ANN Optimization Combinatorial Predication Model,”Operation Research and Management Science, Vol. 14, No. 7, pp. 115-118, Oct. 2005.
[99] Huang X, Ariki Y, Jack M, Hidden Markov Models for speech recognition. Edinburgh University Press,1990.
[100] Jelinek F, Kaufmann M, Mateo C S, Selforganized,“language modelling for speech recognition, in Readings in Speech Recognition,”(Eds. Alex Waibel and Kai-Fu Lee), Morgan Kaufmann, San Mateo, California, 1990, pp. 450-506.
[101] Xie H, Anreae P, Zhang M, Warren P,“Learning Models for English Speech Recognition,”Proceedings of the 27th Conference on Australasian Computer Science, 2004, pp. 323-329.
[102] Liebert M A,“Use of runs statistics for pattern recognition in genomic DNA sequences,”Journal of Computational Biology, vol. 11, pp. 107-124, 2004.
[103] Vinciarelli A and Luettin J,“Off-line cursive script recognition based on continuous density HMM,”Proceedings of the 7th International Workshop on Frontiers in Handwriting Recognition, Amsterdam, 2000, pp. 493-498.
[104] Li Z, Wu Z, He Y and Fulei C,“Hidden Markov model-based fault diagnostics method in speed-up and speed-down process for rotating machinery,”Mechanical Systems and Signal Processing, vol. 19(2), pp. 329-339, 2005.
[105] Rabiner R L,“A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition,”Proceedings of the IEEE, vol. 77(2), pp. 257-286, 1989.
[2] Yang J B, Peng S C. Development of a customer satisfaction evaluation model for construction project management[J]. Building and Environment. 2008, 43(4): 458-468.
[3] Imoto S, Yabuuchi Y, Watada J. Fuzzy regression model of R&D project evaluation[J]. Applied Soft Computing. 2008, 8(3): 1266-1273.
[4] Hwang H S, Yu J C. R&D project evaluation model based on fuzzy set priority[J]. Computers & Industrial Engineering. 1998, 35(3-4): 567-570.
[5]柴中华.电力项目后评价理论、方法及应用研究[D].河海大学, 2007.
[6]辛侨.建设项目后评价研究[D].广东工业大学, 2007.
[7]郎启贵.建设项目可持续性后评价指标体系和方法研究[D].重庆大学, 2006.
[8]蔡成果.项目社会经济效益与影响后评价[D].湖南大学, 2001.
[9]唐镇.农网改造项目后评价理论方法及应用研究[D].华北电力大学(北京), 2003.
[10]杨永东.水电工程项目后评价方法研究[D].华北电力大学(北京), 2003.
[11]曲炜.水利工程项目后评价理论探讨[D].河海大学, 2001.
[12]张宝娟.水利工程项目后评价研究[D].沈阳工业大学, 2006.
[13]韩勇.水利建设项目后评价中的社会评价研究[D].天津大学, 2004.
[14]汪辉德.中小型水利水电工程项目施工后评价探索[D].四川大学, 2005.
[15]王育红.路桥投资项目综合后评价及其应用[D].南京航空航天大学, 2006.
[16]邢妍.完善我国政府投资项目后评价体系的研究[D].北京交通大学, 2007.
[17]吕蓬.大型火电厂项目选址的综合分析与研究[D].华北电力大学, 2002.
[18]谷志红.大唐耒阳发电厂建设项目生产及财务后评价研究[D].华北电力大学(河北), 2006.
[19]赵晓坤.耒阳电厂建设项目影响后评价研究[D].华北电力大学(河北), 2006.
[20]王永利.海勃湾电厂三期工程项目建设实施过程后评价研究[D].华北电力大学(河北), 2007.
[21]黄浩,姜学文,霍红刚.变电建设项目模糊综合评价体系设计的研究[J].湖北电力. 2007, 31(2): 68-70.
[22]凌云鹏.海勃湾电厂三期工程项目经济效益后评价研究[D].华北电力大学(河北), 2007.
[23]李嘉荣.西部城市化投资效率的绿色评价指标体系[J].西南农业大学学报(社会科学版). 2007(02).
[24]程俊军,刘心报,虞孝感, et al.工业园区绿色化若干问题的研究[J].预测. 2006(02).
[25]邓朗妮,黄如寤.基于价值工程的绿色施工方案评价[J].施工技术. 2007(S1).
[26]乔昆,支海波,苏青, et al.绿色项目管理的评价体系研究[J].科技导报. 2005(08).
[27]支海波,乔昆,苏青.关于绿色项目管理评价框架的研究[J].科技导报. 2004(11).
[28]尚金成,张立庆.电力节能减排与资源优化配置技术的研究与应用[J].电网技术. 2007(22).
[29]付强,曾国平,王可俐.特大型工程多项目和谐管理绩效评价体系的构建——以大型国企为例[J].建筑经济. 2007(10).
[30]胡永铨.基于和谐发展观的项目社会评价体系研究[J].科技进步与对策. 2006(01).
[31] Sinuany-stern Z, Amitai A. The post-evaluation of an engineering project via AHP[C]. 1991.
[32] Branley B, Fradin R, Kimbrough S O, et al. On heuristic mapping of decision surfaces for post-evaluation analysis[C]. 1997.
[33] Castro R, Ferreira L. A Comparison Between Chronological and Probabilistic Methods to Estimate Wind Power Capacity Credit[J]. Power Engineering Review, IEEE. 2001, 21(10): 62-62.
[34] Castro R M, Ferreira L A. A comparison between chronological and probabilistic methods to estimate wind power capacity credit[J]. Power Systems, IEEE Transactions on Power Systems. 2001, 16(4): 904-909.
[35] Danech-pajouh M, Sauvadet V. A statistical consistency method for evaluating the output from traffic simulation and forecasting models[C]. 2003.
[36] Eid A, Farag A. A Unified Framework for Performance Evaluation of 3-D Reconstruction Techniques[C]. 2004.
[37] Xuewen T, Sifeng L, Zhigeng F, et al. Research of Rrogram Process Time Post-evaluation Grey Critical Path Algorithm Method Based on Grey Data Advantage Relationship[C]. 2006.
[38] Omori Y, Ito K, Nishida S, et al. Study on Supporting Group Discussions by Improving Discussion Skills with Ex Post Evaluation[C]. 2006.
[39] Yongju C, Changho L, Choonseong L, et al. Development of Evaluation System for Management of Collaborative Information System in Mould Company[C]. 2007.
[40] Yi X, Dongguo S, Yunqing W. Ex-post evaluation analysis of flood control engineering system based on grey relation projection method[C]. 2007.
[41] Burget L, Matejka P, Schwarz P, et al. Analysis of Feature Extraction and Channel Compensation in a GMM Speaker Recognition System[J]. Audio, Speech, and Language Processing, IEEE Transactions on Audio, Speech, and Language Processing. 2007, 15(7): 1979-1986.
[42] Xiao Y, Shao D, Wu Y. The Methodology of Post-Evaluation of River Basin Harnessing Project for Sustainable Development Based on Entropy Theory[C]. 2007.
[43] Song P, Yang Q, Feng B. Application of Entropy Coefficient Optimization Model of Multi-Criteria Decision in Post-Evaluation of Urban Rail Transit[C]. 2007.
[44] Zeng S, Tian M, Li J, et al. Post Evaluation of Water Pollution Control Planning for Huai River Basin in China[C]. 2008.
[45]李泽红,刘利,许淑景.熵权评价法在项目投资决策中的运用[J].会计之友(下). 2007(03).
[46]张朝勇,王卓甫.基于熵权的Fuzzy—AHP法的水电工程投标风险决策[J].水利水电技术. 2007(06).
[47]郭庆军,赛云秀.基于熵权决策的项目方案评价[J].统计与决策. 2007(11).
[48]谢武.基于熵的投影决策法在小水电项目方案择优中的应用[J].东北水利水电. 2005(11).
[49]周书敬,宋喜民.熵权方法在房地产投资环境优序评价中的应用[J].基建优化. 2003(02).
[50]周国良.基于熵的不确定性项目投资决策优化模型[J].重庆大学学报(自然科学版). 2003(11).
[51] Tao Y, Xinmiao Y. Fuzzy comprehensive assessment, fuzzy clustering analysis and its application for urban traffic environment quality evaluation[J]. Transportation Research Part D: Transport and Environment. 1998, 3(1): 51-57.
[52]徐靓,张九根,梁雪春.基于熵权决策法的建筑工程项目投标[J].建筑经济. 2006(S1).
[53]熊光蔚.信息熵在建设工程评标中的应用[J].南昌大学学报(工科版). 2007(04).
[54]杨海云,李珍照,常晓林.水电工程项目评标中的熵权决策法及其应用[J].武汉大学学报(工学版). 2005(02).
[55]易明,周国华,张洁.基于熵权的铁路建设多项目优先级评价[J].铁道运输与经济. 2007(10).
[56] Liang Z, Yang K, Sun Y, et al. Decision support for choice optimal power generation projects: Fuzzy comprehensive evaluation model based on the electricity market[J]. Energy Policy. 2006, 34(17): 3359-3364.
[57]马荣国,刘艳妮.公路建设项目综合评价权重确定方法[J].交通运输工程学报. 2005(02).
[58]陈军飞.应用灰色系统评价方法对港口开发项目综合评价[J].水运工程. 2003(01).
[59]陈雷,王延章.基于熵权系数与TOPSIS集成评价决策方法的研究[J].控制与决策. 2003(04).
[60]王梅,王恒栋,周之豪.信息论与水利建设项目的灰色系统评价[J].河海大学学报(自然科学版). 1997(05).
[61]杨建斌,张慧.大型水利项目风险模糊层次综合评价方法研究[J].人民长江. 2007, 38(6): 148-150.
[62]苏平,马维珍,田元福.模糊综合评价法在项目风险管理中的应用[J].兰州交通大学学报. 2005, 24(6): 53-55.
[63]劳本信,刘宁杰,何庆光.基于模糊风险综合评价法的ERP项目风险评价[J].广西财经学院学报. 2006, 19(4): 72-75.
[64]张星,孙建平,李胜. BOT项目风险的模糊综合评价[J].上海经济研究. 2004: 69-73.
[65]张慧,杨建斌.水利投资项目多目标模糊综合评价方法应用探析[J].长江科学院院报. 2006, 23(5): 52-55.
[66]邹永诚,杨艳群.市政交通项目建设次序的模糊综合评价方法[J].石家庄铁道学院学报. 2003, 16(1): 87-90.
[67]陈岩,付贵,刘铭嘉.公路工程项目风险的模糊综合评价[J].北方交通. 2006: 79-80.
[68]李煜华,郎宏文.高新技术项目投资风险的模糊综合评价模型[J].哈尔滨理工大学学报. 2004, 9(1): 72-75.
[69]李聃菱,李静.房地产项目投资环境模糊综合评价[J].山东建筑工程学院学报. 2004, 19(1): 27-31.
[70]赵旭. AHP与模糊综合评价相结合的商业房地产项目融资风险评价[J].基建优化. 2005, 26(6): 69-71.
[71]周高平,周直,陈远祥.基础设施项目投资风险模糊综合评价模型[J].重庆交通学院学报. 2005, 24(1): 107-111.
[72]杨道箭,齐二石. ERP项目成功度评价体系研究[J].工业工程. 2006(04).
[73]吕滨.贷款项目成功度模糊综合评价法探讨[J].中央财经大学学报. 2000(07).
[74]王兆弘,吕薇,刘建伟.成功度法在产能建设项目后评价中的应用[J].油气田地面工程. 2007(07).
[75]张慧颖.基于灰色变权聚类的公路建设项目成功度评价[J].公路. 2006(08).
[76]陈辉,李军. ANN技术评价技改项目成功度的尝试[J].五邑大学学报(自然科学版). 2003(01).
[77]陈章潮.用时间序列预测电力系统负荷.电力系统自动化,1982,4(6):9~13.
[78]赵宏伟,任震,黄雯莹.基于周期自回归模型的短期负荷预测.中国电机工程学报, 1997,17(5):348~351.
[79]吴宏晓,候志俭.基于免疫支持向量机的电力系统短期负荷预测.电网技术,2004,28(23):47~51.
[80]电网短期负荷预测中的应用.电力系统自动化,2001,25,(l7):32~35,52.
[81]谢宏,陈志业.基于小波分解与气象因素影响的电力系统日负荷预测模型研究.中国电机工程学报,2001,10(5):5~10.
[82]刘颖,田彦芬.保定电网最大负荷及用电量的灰色预测.华北电力技术,1995,6(2):25
[83]张昊,郁滨,吴捷.在预测领域中应用模糊控制的研究.自动化学报, 1999(05).
[84] Niu Dongxiao, Kou Bingen, Chu Ye. The combination forecasting model for power load based on evidential theory. WISM’09-AICI’09, 2009:402-405
[85]张庆宝.基于粗糙集属性约简算法和支持向量机的短期负荷预测.电网技术, 2006(08).
[86]郑永康,陈维荣,戴朝华.小波支持向量机与相空间重构结合的短期负荷预测研究.继电器, 2008(07).
[87]祝志慧,孙云莲,季宇.基于经验模式分解和最小二乘支持向量机的短期负荷预测.继电器, 2007(08).
[88]袁小芳,王耀南.基于混沌优化算法的支持向量机参数选取方法.控制与决策, 2006(01).
[89] Hippert HS, Pedreira CE, Castro R,“Neural networks for short-term load forecasting: a review and evaluation,”IEEE Trans Power Sys, Vol. 16, No. 1, pp.44–55, 2001.
[90] Chen B-J, Chang M-W, Lin C-J,“Load forecasting using support vector machines: a study on EUNITE competition,”IEEE Trans Power Syst, Vol. 19, pp.1821–1830, 2001.
[91] Fan S, Chen L.,“Short-term load forecasting based on an adaptive hybrid method”, IEEE Trans Power Syst, Vol.21, No. 1, pp.392–401, 2006..
[92] Schmtlein K. R.,“Combining Forecasts: Operational Adjustments to Theoretically Optimal rules,”Management Science, Vol. 36, No. 4, pp. 1044-1056, Mar. 1990.
[93] Ji Pei-rong, Zhang Yu-weng, Zhao qing,“Application of Combination Forecast Method to Electric Load Forecasting for Power System,”J of China Three Gorges Univ. (Natural Sciences), Vol. 27, No. 8, pp. 398-400, May.2005.
[94] Wang Ji-quan, Zhao Yu-lin,“Application of Combination Forecasting Method in Power Load Forecast,”Electric Power Automation Equipment, Vol. 24, No. 3, pp. 92-94, Jun. 2004.
[95] Li Lin-chuan, Lv Dong, Wu Wen-jie,“A Linear Combination Based Simplified Load Forecasting Method for Power System,”Power System Technology, Vol. 26, No. 2, pp. 10-13, Dec. 2002.
[96] Ma Yong-kai, Tang Xiao-wo,“Research on the Problem of Optimizing Linear Combination Forecasting Model,”Systems Engineering Theory & Practice, Vol. 9, No. 11, pp. 110-123, Nov. 1998.
[97] Xie Kai-gui, Li Chun-yan , Zhou Jia-qi,“Research of the Combination Forecasting Method for Load Based on Artificial Neural Network,”Proceeding of the CSEE, Vol. 22, No. 4, pp. 85-89, Mar. 2002.
[98] Zhao Hai-qing,“The Application to Power Load Forecasting of ANN Optimization Combinatorial Predication Model,”Operation Research and Management Science, Vol. 14, No. 7, pp. 115-118, Oct. 2005.
[99] Huang X, Ariki Y, Jack M, Hidden Markov Models for speech recognition. Edinburgh University Press,1990.
[100] Jelinek F, Kaufmann M, Mateo C S, Selforganized,“language modelling for speech recognition, in Readings in Speech Recognition,”(Eds. Alex Waibel and Kai-Fu Lee), Morgan Kaufmann, San Mateo, California, 1990, pp. 450-506.
[101] Xie H, Anreae P, Zhang M, Warren P,“Learning Models for English Speech Recognition,”Proceedings of the 27th Conference on Australasian Computer Science, 2004, pp. 323-329.
[102] Liebert M A,“Use of runs statistics for pattern recognition in genomic DNA sequences,”Journal of Computational Biology, vol. 11, pp. 107-124, 2004.
[103] Vinciarelli A and Luettin J,“Off-line cursive script recognition based on continuous density HMM,”Proceedings of the 7th International Workshop on Frontiers in Handwriting Recognition, Amsterdam, 2000, pp. 493-498.
[104] Li Z, Wu Z, He Y and Fulei C,“Hidden Markov model-based fault diagnostics method in speed-up and speed-down process for rotating machinery,”Mechanical Systems and Signal Processing, vol. 19(2), pp. 329-339, 2005.
[105] Rabiner R L,“A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition,”Proceedings of the IEEE, vol. 77(2), pp. 257-286, 1989.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |