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Erschienen in:

2022 | OriginalPaper | Buchkapitel

15. Advanced QUasi-Affine TRansformation Evolutionary (QUATRE) Algorithm and Its Application for Neural Network

verfasst von : Pei Hu, Jeng-Shyang Pan, Shu-Chuan Chu

Erschienen in: Advances in Smart Vehicular Technology, Transportation, Communication and Applications

Verlag: Springer Singapore

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Abstract

The QUasi-Affine TRansformation Evolution (QUATRE) was first proposed by Meng et al. in 2016. It has the characteristics of few parameters and fast convergence. This paper brings two methods to improve its solution quality. The opposite position and comprehensive learning greatly advance the ability of jumping out of local traps when the QUATRE falls into stagnation. Their performance is verified by 23 benchmark functions. In the end, they succeed to train the parameters of neural network and predict the long-term traffic flow in Qingdao.

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Vorheriges Kapitel QUasi-Affine TRansformation Evolutionary Algorithm for Feature Selection

Nächstes Kapitel An QUasi-Affine TRansformation Evolution (QUATRE) Algorithm for Job-Shop Scheduling Problem by Mixing Different Strategies

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Titel: Advanced QUasi-Affine TRansformation Evolutionary (QUATRE) Algorithm and Its Application for Neural Network
verfasst von: Pei Hu
Jeng-Shyang Pan
Shu-Chuan Chu
Verlag: Springer Singapore
Buch: Advances in Smart Vehicular Technology, Transportation, Communication and Applications
Print ISBN: 978-981-16-4038-4

Electronic ISBN: 978-981-16-4039-1

Copyright-Jahr: 2022
DOI: https://doi.org/10.1007/978-981-16-4039-1_15

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