Algorithm Research & Explore
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362-366

Application of RBFNN based on TSDPCA in monthly runoff forecasting

Jiang Linli1,2
Wu Jiansheng1
Ding Lixin2
1. School of Mathematics & Computer Science, Guangxi Science & Technology Normal University, Laibin Guangxi 546199, China
2. State Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, China

Abstract

Aiming at the shortages of the RBFNN network structure and initial data center being difficult to objectively determined, this paper put forward using two searching density peak clustering algorithm(TSDPCA) to find data center value and number as the initial parameters of RBFNN and the number of hidden layer nodes quickly, and finally used gradient descent method of optimization the structure of RBFNN and various parameters to set up precipitation forecast model, which was applied in forecasting monthly rainfall of Guangxi, aiming at testing the effectiveness of the model. The result shows that the mean relative error of TSDPCA-RBFNN forecasting is decreased by 10%~35% compared with K-RBFNN and OLS-RBFNN model, which has better prediction performance.

Foundation Support

广西自然科学基金资助项目(2014GXNSFAA118027)
广西高校科学技术研究项目(YB2014467)
广西高校中青年教师基础能力提升项目(2017KY0896)
广西重点学科资助项目(070105)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.07.0708
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 2
Section: Algorithm Research & Explore
Pages: 362-366
Serial Number: 1001-3695(2019)02-011-0362-05

Publish History

[2019-02-05] Printed Article

Cite This Article

蒋林利, 吴建生, 丁立新. 基于二分搜索密度峰算法的RBFNN在月降水预报中的应用 [J]. 计算机应用研究, 2019, 36 (2): 362-366. (Jiang Linli, Wu Jiansheng, Ding Lixin. Application of RBFNN based on TSDPCA in monthly runoff forecasting [J]. Application Research of Computers, 2019, 36 (2): 362-366. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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