A collective neurodynamic optimization approach to bound-constrained nonconvex optimization

Neural Networks

Volumn 55, Issue , 2014, Pages 20-29

  Yan, Zheng ^a   Wang, Jun ^a,b   Li, Guocheng ^c  

^a CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

^b DALIAN UNIVERSITY OF TECHNOLOGY   (China)

^c BEIJING INFORMATION SCIENCE AND TECHNOLOGY UNIVERSITY   (China)

Author keywords

Collective neurodynamic optimization; Nonconvex optimization; Recurrent neural network

Indexed keywords

COMPUTATIONAL EFFICIENCY; CONSTRAINED OPTIMIZATION; ITERATIVE METHODS; NETWORK LAYERS; PARTICLE SWARM OPTIMIZATION (PSO);

CONSTRAINED NONCONVEX OPTIMIZATIONS; CONSTRAINED OPTIMI-ZATION PROBLEMS; EVOLUTIONARY APPROACH; GLOBAL OPTIMAL SOLUTIONS; NEURODYNAMIC OPTIMIZATIONS; NONCONVEX OPTIMIZATION; NONCONVEX OPTIMIZATION PROBLEM; PROJECTION NEURAL NETWORK;

RECURRENT NEURAL NETWORKS;

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; COLLECTIVE NEURODYNAMIC OPTIMIZATION; EVOLUTIONARY ALGORITHM; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; PRIORITY JOURNAL; PROCESS DEVELOPMENT; PROCESS OPTIMIZATION; QUALITY CONTROL; ALGORITHM; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; GROUP PROCESS; PROBLEM SOLVING; STANDARDS; VALIDATION STUDY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; GROUP PROCESSES; NEURAL NETWORKS (COMPUTER); PROBLEM SOLVING;

EID: 84897517330     PISSN: 08936080     EISSN: 18792782     Source Type: Journal    
DOI: 10.1016/j.neunet.2014.03.006     Document Type: Article

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