Titlebook: Bio-Inspired Computing: Theories and Applications; 16th International C Linqiang Pan,Zhihua Cui,Lianghao Li Conference proceedings 2022 Spr

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书目名称Bio-Inspired Computing: Theories and Applications影响因子(影响力)

书目名称Bio-Inspired Computing: Theories and Applications影响因子(影响力)学科排名

书目名称Bio-Inspired Computing: Theories and Applications网络公开度

书目名称Bio-Inspired Computing: Theories and Applications网络公开度学科排名

书目名称Bio-Inspired Computing: Theories and Applications被引频次

书目名称Bio-Inspired Computing: Theories and Applications被引频次学科排名

书目名称Bio-Inspired Computing: Theories and Applications年度引用

书目名称Bio-Inspired Computing: Theories and Applications年度引用学科排名

书目名称Bio-Inspired Computing: Theories and Applications读者反馈

书目名称Bio-Inspired Computing: Theories and Applications读者反馈学科排名

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Black Widow Spider Algorithm Based on Differential Evolution and Random Disturbancential evolution strategy is introduced to avoid unnecessary exploration. At the same time, the random disturbance factor is used to improve the local exploitation performance of the black widow algorithm, and the memory function is added to the individual to improve the population‘s reproductive str

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A Cuckoo Quantum Evolutionary Algorithm for the Graph Coloring Problem A cuckoo quantum evolutionary algorithm (CQEA) is proposed for the GCP, which is based on the framework of quantum-inspired evolutionary algorithm. To reduce iterations for the search of the chromatic number, the initial quantum population is generated with random initialization assisted by inherit

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Feature Selection Algorithm Based on Discernibility Matrix and Fruit Fly Optimization can quickly search for feature subsets, effectively reducing the computational workload; However, in some decision tables of this type of method, there were also problems such as the searched feature subset containing redundant features, which led to a decrease in accuracy. Aiming at such problems

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Implementation and Application of NSGA-III Improved Algorithm in Multi-objective Environmentr more objectives) has gradually become a hot spot. NSGA-III algorithm is effective in dealing with evolutionary multi-objective optimization problems. In this paper, we recognize some advantages of the existing NSGA-III algorithm and make some improvements. The improved NSGA-III algorithm has highe

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Titlebook: Bio-Inspired Computing: Theories and Applications; 16th International C Linqiang Pan,Zhihua Cui,Lianghao Li Conference proceedings 2022 Spr

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