Chebyshev neural network model with linear and nonlinear active functions

S. S. Chaharborj, Y. Mahmoudi
{"title":"Chebyshev neural network model with linear and nonlinear active functions","authors":"S. S. Chaharborj, Y. Mahmoudi","doi":"10.14419/IJBAS.V5I3.6382","DOIUrl":null,"url":null,"abstract":"In this paper the second order non-linear ordinary differential equations of Lane-Emden type as singular initial value problems using Chebyshev Neural Network (ChNN) with linear and nonlinear active functions has been studied. Active functions as, \\(\\texttt{F(z)=z}, \\texttt{sinh(x)}, \\texttt{tanh(z)}\\) are considered to find the numerical results with high accuracy. Numerical results from Chebyshev Neural Network shows that linear active function has more accuracy and is more convenient compare to other functions.","PeriodicalId":14296,"journal":{"name":"International Journal of Sciences: Basic and Applied Research","volume":"14 1","pages":"182-187"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Sciences: Basic and Applied Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14419/IJBAS.V5I3.6382","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

In this paper the second order non-linear ordinary differential equations of Lane-Emden type as singular initial value problems using Chebyshev Neural Network (ChNN) with linear and nonlinear active functions has been studied. Active functions as, \(\texttt{F(z)=z}, \texttt{sinh(x)}, \texttt{tanh(z)}\) are considered to find the numerical results with high accuracy. Numerical results from Chebyshev Neural Network shows that linear active function has more accuracy and is more convenient compare to other functions.
具有线性和非线性主动函数的切比雪夫神经网络模型
本文利用具有线性和非线性主动函数的切比雪夫神经网络研究了二阶非线性Lane-Emden型常微分方程的奇异初值问题。为了得到精度较高的数值结果,考虑了\(\texttt{F(z)=z}, \texttt{sinh(x)}, \texttt{tanh(z)}\)等主动函数。切比雪夫神经网络的数值结果表明,与其他函数相比,线性主动函数具有更高的精度和方便性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信