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Bio-Inspired Collaborative Intelligent Control and Optimization pp 393–469Cite as

Bio-Inspired Bi-Directional Optimization Algorithms

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Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 118))

Abstract

In this chapter, based on different biological mechanisms, some bi-directional optimization methods are proposed. Firstly, a bi-directional optimization method based on an immune-enhanced neural network is introduced. Then, a hybrid approach of genetic algorithm (GA) and improved particle swarm optimization (IPSO) is proposed to construct the radial basis function neural network (RNN). Next, a bi-directional prediction approach based on neural networks and multi-objective evolutionary algorithm is developed. At last, a bi-directional prediction model based on a support vector machine (SVM) and improved particle swarm optimization algorithm (SVM-IPSO) is created.

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Authors and Affiliations

  1. College of Information Science and Technology, Donghua University, Shanghai, China

    Yongsheng Ding

  2. College of Information Science and Technology, Donghua University, Shanghai, China

    Lei Chen

  3. College of Information Science and Technology, Donghua University, Shanghai, China

    Kuangrong Hao

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  1. Yongsheng Ding
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  2. Lei Chen
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  3. Kuangrong Hao
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Correspondence to Yongsheng Ding .

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Ding, Y., Chen, L., Hao, K. (2018). Bio-Inspired Bi-Directional Optimization Algorithms. In: Bio-Inspired Collaborative Intelligent Control and Optimization. Studies in Systems, Decision and Control, vol 118. Springer, Singapore. https://doi.org/10.1007/978-981-10-6689-4_9

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  • DOI: https://doi.org/10.1007/978-981-10-6689-4_9

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