{"title":"具有线性和非线性主动函数的切比雪夫神经网络模型","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":"{\"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}","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}
Chebyshev neural network model with linear and nonlinear active functions
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.