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Neural network based on improved parallel bat algorithm and its application

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dc.contributor.authorZhao, Z.Q.
dc.contributor.authorLiu, S.J.
dc.contributor.authorXu, L.
dc.contributor.authorPan, J.S.
dc.date.issued2021
dc.description.abstractThe artificial neural network is a research hotspot emerging in the field of artificial intelligence. Back Propagation (BP) neural network plays an important role in neural network. The network has the disadvantages of slow convergence of learning algorithms and easy falling into a local minimum. In this paper, a parallel bat algorithm with a new communication strategy is proposed, which is used to optimize the weights and thresholds of the BP neural network and establish the improved PBA-BP model. It was applied to optimize the parameters of the PID controller. Finally, we verified the effectiveness of the proposed method through the simulations.
dc.identifier.citationJournal of Network Intelligence, 2021; 6(3):428-439
dc.identifier.issn2414-8105
dc.identifier.issn2414-8105
dc.identifier.urihttps://hdl.handle.net/11541.2/26762
dc.language.isoen
dc.publisherTaiwan Ubiquitous Information
dc.relation.fundingNational Natural Science Foundations of China 61872085
dc.relation.fundingScientific Research Project of Fujian Education Department JK2017029
dc.relation.fundingScientific Research and Development Foundation of Fujian University of Technology GY-Z18181
dc.rightsCopyright 2021 Taiwan Ubiquitous Information
dc.source.urihttp://bit.kuas.edu.tw/~jni/2021/vol6/s3/03.JNI-0206.pdf
dc.subjectBP neural network
dc.subjectparallel bat algorithm
dc.subjectcommunication strategy
dc.subjectparameter optimization
dc.subjectPID control
dc.titleNeural network based on improved parallel bat algorithm and its application
dc.typeJournal article
pubs.publication-statusPublished
ror.mmsid9916563088401831

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