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Titlebook: Advances in Swarm Intelligence; 10th International C Ying Tan,Yuhui Shi,Ben Niu Conference proceedings 2019 Springer Nature Switzerland AG

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0302-9743 m and differential evolution; swarm robotics...Part II: Multi-agent system; multi-objective optimization; neural networks; machine learning; identification and recognition; social computing and knowledge graph; service quality and energy management..978-3-030-26368-3978-3-030-26369-0Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Rajnish Sharma,Archana Mantri,Sumeet Duaof system under investigation with discrete distributions, which takes into account the draw effect in competition, is built. Recursive procedure, which permits rather exactly simulate a functioning of the system as a whole, is worked out. Method of numerical analysis, arising from digital model is schematically described.
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https://doi.org/10.1007/978-3-319-65987-9 computational results indicated that both main effect and interactions were statistically significant with a 95% confidence interval. The MCPSO outperformed the other variants of PSO for most datasets whilst the computational times required by all variants were moderately difference.
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An Inter-Peer Communication Mechanism Based Water Cycle Algorithmther four heuristic algorithms are involved to test on eight benchmark functions. Experimental results show that IPCWCA performs better on solving different types of problems compared with other four algorithms.
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Niching Particle Swarm Optimizer with Entropy-Based Exploration Strategy for Global Optimizationors. To validate the effectiveness of the proposed algorithm, extensive experiments have been conducted based on 28 benchmarks from CEC’ 2013. The proposed algorithm shows its competitive performance with comparing to six other typical variants of PSO.
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