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

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書目名稱Evolutionary Algorithms and Neural Networks影響因子(影響力)




書目名稱Evolutionary Algorithms and Neural Networks影響因子(影響力)學(xué)科排名




書目名稱Evolutionary Algorithms and Neural Networks網(wǎng)絡(luò)公開度




書目名稱Evolutionary Algorithms and Neural Networks網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Evolutionary Algorithms and Neural Networks被引頻次




書目名稱Evolutionary Algorithms and Neural Networks被引頻次學(xué)科排名




書目名稱Evolutionary Algorithms and Neural Networks年度引用




書目名稱Evolutionary Algorithms and Neural Networks年度引用學(xué)科排名




書目名稱Evolutionary Algorithms and Neural Networks讀者反饋




書目名稱Evolutionary Algorithms and Neural Networks讀者反饋學(xué)科排名

光明正大

Book 2019 algorithms for several purposes such as classification, clustering, approximation, and prediction problems. It provides a tutorial on how to design, adapt, and evaluate artificial neural networks as well, and includes source codes for most of the proposed techniques as supplementary materials..

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Biogeography-Based Optimisationlarly to other evolutionary algorithms, BBO has been equipped with crossover and mutations. The main difference between this algorithm and GA is the use of two operators to perform crossover and exploitation. The concepts of mutation is also similar, in which small changes occur in variables of solu

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滲透

Evolutionary Deep Neural Networksms are then applied to the datasets for classification. The chapter also considers the comparison and analysis of different evolutionary algorithms for classifying datasets as well. Another contribution is finding the best set of features for the dataset using evolutionary algorithms. The results sh

Affiliation

,Erwerbst?tige Frauen als Problemgruppe,lutionary Algorithms are able to efficiently classify the dataset with a very high accuracy and convergence speed. It was also observed that feature selection is important and evolutionary algorithms are able to find the optimal set of features for this problem.

Affiliation

ornithology

https://doi.org/10.1007/978-3-8350-5527-8tions. However, each solution in BBO faces different mutation rates depending on its fitness, which makes it different from the GA algorithm. In this chapter, the inspiration and mathematical equations of the BBO algorithm are first given. A set of problems is then solved with this algorithm to observe and analyse its performance.

Hallmark

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