A new bio-inspired optimization algorithm based on the self-defense mechanism of plants in nature [electronic resource] / by Camilo Caraveo, Fevrier Valdez, Oscar Castillo.
- 作者： Caraveo, Camilo.
- 其他作者：
- 其他題名：
- SpringerBriefs in computational intelligence.
- 出版： Cham : Springer International Publishing :Imprint: Springer 2019.
- 叢書名： SpringerBriefs in computational intelligence,
- 主題： Mathematical optimization. , Algorithms. , Plant defenses--Mathematical models. , Computational Intelligence. , Artificial Intelligence. , Plant Sciences. , Optimization.
- ISBN： 9783030055516 (electronic bk.) 、 9783030055509 (paper)
- URL：
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電子書(校內)
- 一般註：Introduction -- Theory and Background -- Self-defense of the Plants -- Predator-prey mode -- Proposed Method -- Case studies -- Conclusions. E1084學校採購電子書
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讀者標籤：
- 系統號： 000274391 | 機讀編目格式
館藏資訊
This book presents a new meta-heuristic algorithm, inspired by the self-defense mechanisms of plants in nature. Numerous published works have demonstrated the various self-defense mechanisms (survival strategies) plants use to protect themselves against predatory organisms, such as herbivorous insects. The proposed algorithm is based on the predator–prey mathematical model originally proposed by Lotka and Volterra, consisting of two nonlinear first-order differential equations, which allow the growth of two interacting populations (prey and predator) to be modeled. The proposed meta-heuristic is able to produce excellent results in several sets of benchmark optimization problems. Further, fuzzy logic is used for dynamic parameter adaptation in the algorithm.
摘要註
This book presents a new meta-heuristic algorithm, inspired by the self-defense mechanisms of plants in nature. Numerous published works have demonstrated the various self-defense mechanisms (survival strategies) plants use to protect themselves against predatory organisms, such as herbivorous insects. The proposed algorithm is based on the predator-prey mathematical model originally proposed by Lotka and Volterra, consisting of two nonlinear first-order differential equations, which allow the growth of two interacting populations (prey and predator) to be modeled. The proposed meta-heuristic is able to produce excellent results in several sets of benchmark optimization problems. Further, fuzzy logic is used for dynamic parameter adaptation in the algorithm.