Cultural Swarms for Optimization - Daneshyari, Moayed Daniel
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Swarm intelligence is the collective behavior of self-organized agents. In this book, a computational paradigm is proposed that adopts the particle swarm optimization within a cultural framework. The cultural algorithm adopted here consists of two space, population space and belief space including five knowledge sections: situational knowledge, normative knowledge, topographical knowledge, history knowledge, and domain knowledge. Several innovative paradigms are proposed that use the proposed cultural swarm for single objective optimization, constrained optimization, multiobjective optimization, and dynamic optimization.…mehr

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Produktbeschreibung
Swarm intelligence is the collective behavior of self-organized agents. In this book, a computational paradigm is proposed that adopts the particle swarm optimization within a cultural framework. The cultural algorithm adopted here consists of two space, population space and belief space including five knowledge sections: situational knowledge, normative knowledge, topographical knowledge, history knowledge, and domain knowledge. Several innovative paradigms are proposed that use the proposed cultural swarm for single objective optimization, constrained optimization, multiobjective optimization, and dynamic optimization.
Autorenporträt
Moayed Daniel Daneshyari is currently a faculty at Elizabeth City State University in Elizabeth City, North Carolina. His area of research interests are in neural network, swarm intelligence, multiobjective optimization, chaotic dynamics, biological modeling, and robotics.