A Novel Real-coded Quantum-inspired Genetic Algorithm and Its Application in Data Reconciliation

被引:5
|
作者
Gao Lin [1 ,2 ]
Gu Xingsheng [1 ]
机构
[1] E China Univ Sci & Technol, Res Inst Automat, Shanghai 200237, Peoples R China
[2] Qingdao Univ Sci & Technol, Sch Automat & Elect Engn, Qingdao 266042, Peoples R China
基金
国家高技术研究发展计划(863计划);
关键词
quantum-inspired genetic algorithm; real-coded; interval division; nonlinear data reconciliation; DYNAMIC DATA RECONCILIATION; GROSS ERROR-DETECTION; EVOLUTIONARY ALGORITHM; OPTIMIZATION; NETWORK;
D O I
10.1080/18756891.2012.696893
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Traditional quantum-inspired genetic algorithm (QGA) has drawbacks such as premature convergence, heavy computational cost, complicated coding and decoding process etc. In this paper, a novel real-coded quantum-inspired genetic algorithm is proposed based on interval division thinking. Detailed comparisons with some similar approaches for some standard benchmark functions test validity of the proposed algorithm. Besides, the proposed algorithm is used in two typical nonlinear data reconciliation problems (distilling process and extraction process) and simulation results show its efficiency in nonlinear data reconciliation problems.
引用
收藏
页码:413 / 420
页数:8
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