Internet of things financial data capture technology based on improved particle swarm optimization FLFNN

被引：2
|
作者：
Ye T. [1 ]
机构：
[1] College of International Finance and Bank, University of Science and Technology LiaoNing, Anshan, Liaoning
来源：
International Journal of Computers and Applications | 2020年 / 42卷 / 01期
关键词：
capture; financial data; functional link fuzzy neural network; Internet of things; Particle swarm;
D O I：
10.1080/1206212X.2017.1397389
中图分类号：
学科分类号：
摘要：
One Internet of things financial data capture technology based on improved particle swarm optimization functional link fuzzy neural network (FLFNN) has been proposed to improve the performance of Internet of things financial data capture algorithm as well as the accuracy of data capture. First, research on FLFNN and particle swarm optimization algorithm has been made and improvement for the learning process of FLFNN model parameter with adoption of particle swarm optimization algorithm has been made; second, one particle swarm optimization algorithm based on parameter self-adjusting has been proposed to improve the calculation efficiency and convergence performance of particle swarm optimization algorithm; last, effective verification has been made for all data capture algorithms by studying one case of Internet of things financial data capture. © 2017, © 2017 Informa UK Limited, trading as Taylor & Francis Group.
引用
收藏
页码：102 / 107
页数：5
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