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·728 智能系统学报 第10卷 [2]ABKENAR S M S,CHASE D V,STANLEY S D,et al. [14]COELHO B.ANDRADE-CAMPOS A.Efficiency achieve- Optimizing pumping system for sustainable water distribution ment in water supply systems-a review[J].Renewable network by using genetic algorithm[C]//2013 International and Sustainable Energy Reviews,2014,30:59-84. Green Computing Conference.Arlington,USA,2013:1-6. [15]ANNELIES D C,KENNETH S.Optimisation of gravity-fed [3]BLINCO L J,SIMPSON A R,LAMBERT M F,et al.Ge- water distribution network design:a critical review [J]. netic algorithm optimization of operational costs and green- European Journal of Operational Research,2013,228 house gas emissions for water distribution systems[J].Pro- (1):1-10. cedia Engineering,2014,89:509-516. [16]李宁,孙德宝,邹彤,等.基于差分方程的PS0算法粒 [4]DINARDO A.DINATALE M,GRECO R,et al.Ant algo- 子运动轨迹分析[J].计算机学报,2006,29(11): rithm for smart water network partitioning[J].Procedia En- 2052-2061. gineering,2014,70:525-534. LI Ning,SUN Debao,ZOU Tong,et al.An analysis for a [5]MOOSAVIAN N,ROODSARI B K.Soccer league competi- particle's trajectory of PSO based on difference equation tion algorithm:a novel meta-heuristic algorithm for optimal [J].Chinese Journal of Computers,2006,29(11):2052- design of water distribution networks[J.Swarm and Evolu- 2061. tionary Computation,2014,17:14-24. [17]VANDEN BERGH F.An analysis of particle swarm optimi- [6]LIU Boning,RECKHOW D A,LI Yun.A two-site chlorine zers[D].Pretoria,South Africa:University of Pretoria, decay model for the combined effects of pH,water distribu- 2002:81-83. tion temperature and in-home heating profilesusing differen- [18]SEDKI A,OUAZAR D.Hybrid particle swarm optimiza- tial evolution[J].Water Research,2014,53:47-57. tion and differential evolution for optimal design of water [7]NASER M,ROODSARIB K.Soccer league competition al- distribution systems[J].Advanced Engineering Informat- gorithm:A novel meta-heuristic algorithm for optimal design ic8,2012,26(3):582-591. of water distribution networks[J].Swarm and Evolutionary [19]SAVIC D A,WALTERS G A.Genetic algorithms for least Computation,2014,17:14-24. cost design of water distribution networks[J].Joumal of [8]WANG Hongxiang,GUO Wenxian.Calibrating chlorine wall Water Resources Planning and Management,1997,123 decay coefficients of water distribution systems based on hy- (2):67-77. brid PSO C//Sixth International Conference on Natural [20]IDEL M,JOAQUIN I,RAFAEL P G,et al.Improved per- Computation (ICNC).Yantai,China,2010:3856-3860. formance of PSO with self-adaptive parameters for compu- [9]MONTALVO I M,IZQUIERDO J,PEREZ R,et al.A di- ting the optimal design of water supply systems[].Engi- versity-enriched variant of discrete PSO applied to the de- neering Applications of Artificial Intelligence,2010,23 sign of water distribution networks[].Engineering Optimi- (5):727-735. zation,2008,40(7):655-668. [21]SURIBABU C R.Differential evolution algorithm for opti- [10 ZARGHAMIM,HAJYKAZEMIAN H.Urban water re- mal design of water distribution networks[J].Journal of sources planning by using a modified particle swarm optimi- Hydroinformatics,2010.12(1):66-82. zation algorithm [J].Resources,Conservation and Recy- 作者简介: cling,.2013,70:1-8. 王超,男,1987年生,硕士研究生, [11]HASHEMI A B,MEYBODI M R.A note on the learning 主要研究方向为智能计算和智能优化 automata based algorithms for adaptive parameter selection 算法。 in PSO[J].Applied Soft Computing,2011,11(1):689- 705. [12]DE FATIMA ARAUJO T,UTURBEY W.Performance as- sessment of PSO,DE and hybrid PSO-DE algorithms when applied to the dispatch of generation and demand[].Inter- 乔俊飞,男,1968年生,教授,博士 national Journal of Electrical Power Energy Systems, 主要研究方向为复杂过程建模、优化与 2013,47:205-217. 控制和智能优化控制。主持国家自然 [13]刘建华,樊晓平,瞿志华.一种基于相似度的新型粒子 科学基金项目2项、国家“863”计划项 群算法[J].控制与决策,2007,22(10):1155-1159. 目2项,发表学术论文100余篇,出版 LIU Jianhua,FAN Xiaoping,QU Zhihua.A new particle 专著2部,获国家发明专利授权15项。 swarm optimization algorithm based on similarity[J].Con- trol and Decision,2007,22(10):1155-1159.[2] ABKENAR S M S, CHASE D V, STANLEY S D, et al. Optimizing pumping system for sustainable water distribution network by using genetic algorithm[C] / / 2013 International Green Computing Conference. Arlington, USA, 2013: 1⁃6. [3]BLINCO L J, SIMPSON A R, LAMBERT M F, et al. Ge⁃ netic algorithm optimization of operational costs and green⁃ house gas emissions for water distribution systems[J]. Pro⁃ cedia Engineering, 2014, 89: 509⁃516. [4] DINARDO A, DINATALE M, GRECO R, et al. Ant algo⁃ rithm for smart water network partitioning[J]. Procedia En⁃ gineering, 2014, 70: 525⁃534. [5]MOOSAVIAN N, ROODSARI B K. Soccer league competi⁃ tion algorithm: a novel meta⁃heuristic algorithm for optimal design of water distribution networks[J]. Swarm and Evolu⁃ tionary Computation, 2014, 17: 14⁃24. [6] LIU Boning, RECKHOW D A, LI Yun. A two⁃site chlorine decay model for the combined effects of pH, water distribu⁃ tion temperature and in⁃home heating profilesusing differen⁃ tial evolution[J]. Water Research, 2014, 53: 47⁃57. [7] NASER M, ROODSARIB K. Soccer league competition al⁃ gorithm: A novel meta⁃heuristic algorithm for optimal design of water distribution networks[ J]. Swarm and Evolutionary Computation, 2014, 17: 14⁃24. [8]WANG Hongxiang, GUO Wenxian. Calibrating chlorine wall decay coefficients of water distribution systems based on hy⁃ brid PSO [ C] / / Sixth International Conference on Natural Computation (ICNC). Yantai, China, 2010: 3856⁃3860. [9] MONTALVO I M, IZQUIERDO J, PÉREZ R, et al. A di⁃ versity⁃enriched variant of discrete PSO applied to the de⁃ sign of water distribution networks[J]. Engineering Optimi⁃ zation, 2008, 40(7): 655⁃668. [ 10 ] ZARGHAMIM, HAJYKAZEMIAN H. Urban water re⁃ sources planning by using a modified particle swarm optimi⁃ zation algorithm [ J]. Resources, Conservation and Recy⁃ cling, 2013, 70: 1⁃8. [11] HASHEMI A B, MEYBODI M R. A note on the learning automata based algorithms for adaptive parameter selection in PSO[J]. Applied Soft Computing, 2011, 11(1): 689⁃ 705. [12] DE FÁTIMA ARAU ' JO T, UTURBEY W. Performance as⁃ sessment of PSO, DE and hybrid PSO⁃DE algorithms when applied to the dispatch of generation and demand[J]. Inter⁃ national Journal of Electrical Power & Energy Systems, 2013, 47: 205⁃217. [13]刘建华, 樊晓平, 瞿志华. 一种基于相似度的新型粒子 群算法[J]. 控制与决策, 2007, 22(10): 1155⁃1159. LIU Jianhua, FAN Xiaoping, QU Zhihua. A new particle swarm optimization algorithm based on similarity[ J]. Con⁃ trol and Decision, 2007, 22(10): 1155⁃1159. [14]COELHO B, ANDRADE⁃CAMPOS A. Efficiency achieve⁃ ment in water supply systems—a review [ J]. Renewable and Sustainable Energy Reviews, 2014, 30: 59⁃84. [15]ANNELIES D C, KENNETH S. Optimisation of gravity⁃fed water distribution network design: a critical review [ J]. European Journal of Operational Research, 2013, 228 (1): 1⁃10. [16]李宁, 孙德宝, 邹彤, 等. 基于差分方程的 PSO 算法粒 子运动轨迹分析[ J]. 计算机学报, 2006, 29 ( 11): 2052⁃2061. LI Ning, SUN Debao, ZOU Tong, et al. An analysis for a particle􀆳s trajectory of PSO based on difference equation [J]. Chinese Journal of Computers, 2006, 29(11): 2052⁃ 2061. [17]VANDEN BERGH F. An analysis of particle swarm optimi⁃ zers [ D]. Pretoria, South Africa:University of Pretoria, 2002: 81⁃83. [18] SEDKI A, OUAZAR D. Hybrid particle swarm optimiza⁃ tion and differential evolution for optimal design of water distribution systems [ J]. Advanced Engineering Informat⁃ ics, 2012, 26(3): 582⁃591. [19] SAVIC D A, WALTERS G A. Genetic algorithms for least cost design of water distribution networks [ J]. Journal of Water Resources Planning and Management, 1997, 123 (2): 67⁃77. [ 20]IDEL M, JOAQUIN I, RAFAEL P G, et al. Improved per⁃ formance of PSO with self⁃adaptive parameters for compu⁃ ting the optimal design of water supply systems[ J]. Engi⁃ neering Applications of Artificial Intelligence, 2010, 23 (5): 727⁃735. [21] SURIBABU C R. Differential evolution algorithm for opti⁃ mal design of water distribution networks [ J]. Journal of Hydroinformatics, 2010, 12(1): 66⁃82. 作者简介: 王超,男,1987 年生,硕士研究生, 主要研究方向为智能计算和智能优化 算法。 乔俊飞,男,1968 年生,教授,博士, 主要研究方向为复杂过程建模、优化与 控制和智能优化控制。 主持国家自然 科学基金项目 2 项、国家“863”计划项 目 2 项,发表学术论文 100 余篇,出版 专著 2 部,获国家发明专利授权 15 项。 ·728· 智 能 系 统 学 报 第 10 卷
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