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Titlebook: Evolutionary Algorithms and Neural Networks; Theory and Applicati Seyedali Mirjalili Book 2019 Springer International Publishing AG, part o

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21#
發(fā)表于 2025-3-25 05:01:57 | 只看該作者
Evolutionary Algorithms and Neural Networks978-3-319-93025-1Series ISSN 1860-949X Series E-ISSN 1860-9503
22#
發(fā)表于 2025-3-25 08:23:17 | 只看該作者
23#
發(fā)表于 2025-3-25 13:10:38 | 只看該作者
24#
發(fā)表于 2025-3-25 17:08:04 | 只看該作者
https://doi.org/10.1007/978-3-322-92630-2Ant Colony Optimisation (ACO) is one of the well-known swarm intelligence techniques in the literature. This chapter discusses the inspiration and mathematical model of several valiants of this algorithm. To analyse the performance of ACO, it is applied to several Travailing Salesman Problem (TSP).
25#
發(fā)表于 2025-3-25 23:32:10 | 只看該作者
Deutsches Zentrum für AltersfragenGenetic Algorithm (GA) is one of the first population-based stochastic algorithm proposed in the history. Similar to other EAs, the main operators of GA are selection, crossover, and mutation. This chapter briefly presents this algorithm and applies it to several case studies to observe its performance.
26#
發(fā)表于 2025-3-26 02:25:29 | 只看該作者
Prozess der Implementierung und Umsetzung,Feedforward Neural Networks (FNN) have been of the most popular NNs with a wide range of applications. The process of finding optimal values for controlling parameters of a NN is called training and can be considered as an optimisation problem. This chapter trains FNNs using several optimisation algorithms.
27#
發(fā)表于 2025-3-26 07:17:00 | 只看該作者
28#
發(fā)表于 2025-3-26 09:47:12 | 只看該作者
29#
發(fā)表于 2025-3-26 16:18:15 | 只看該作者
30#
發(fā)表于 2025-3-26 17:39:11 | 只看該作者
Ant Colony OptimisationAnt Colony Optimisation (ACO) is one of the well-known swarm intelligence techniques in the literature. This chapter discusses the inspiration and mathematical model of several valiants of this algorithm. To analyse the performance of ACO, it is applied to several Travailing Salesman Problem (TSP).
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