A new approach of obtaining reservoir operation rules: Artificial immune recognition system

被引:12
|
作者
Wang, Xiao-Lin [1 ]
Cheng, Jin-Hua [1 ]
Yin, Zheng-Jie [2 ]
Guo, Ming-Jing [1 ]
机构
[1] China Univ Geosci, Sch Econ & Management, Wuhan 430074, Peoples R China
[2] Yangtze River Sci Res Inst, Water Resource Dept, Wuhan 430010, Peoples R China
关键词
Operating rules; Water-supply reservoir; Artificial immune recognition system (AIRS); Classification performance;
D O I
10.1016/j.eswa.2011.03.055
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Artificial immune recognition system (AIRS) was employed in this paper as a new approach of data mining to extract operating rules on a case of water-supply reservoir, and the comparisons were performed between the operating rules obtained by the system and those by RBF. Further statistics about distance distributions between the acquired operating rules and training or testing samples are made to indirectly illuminate the impacts on the performances or behaviors of AIRS from three aspects of different affinity functions, training (testing) sample spatial distribution and supplementary samples in high nonlinear space of operation decision. The results indicate that AIRS can effectively extract water-supply operating rules and enrich the reservoir operation researches. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:11701 / 11707
页数:7
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