{"title":"PEMFC的NNARX模型采用神经网络剪枝模型结构","authors":"Shan-Jen Cheng, J. Miao, Te-Jen Chang","doi":"10.18178/IJOEE.4.1.1-5","DOIUrl":null,"url":null,"abstract":"The paper presents a nonlinear modeling of the PEMFC using Neural Network Auto-Regressive model with eXogenous inputs (NNARX) approach. The Multilayer Perception (MLP) network is applied to evaluate the structure of the NNARX model of PEMFC. The NNARX model structure is according to the Optimal Brain Surgeon (OBS) methodology to indicate the significant network structure. The validity and accuracy of NNARX model are tested by one step ahead relating output voltage to input current from measured experimental of PEMFC. The results show that the obtained nonlinear NNARX model based on OBS technique can efficiently approximate the dynamic mode of the PEMFC and model output and system measured output consistently. ","PeriodicalId":13951,"journal":{"name":"International Journal of Electrical Energy","volume":"16 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"NNARX Model of the PEMFC Used Neural Network Pruning Model Structure\",\"authors\":\"Shan-Jen Cheng, J. Miao, Te-Jen Chang\",\"doi\":\"10.18178/IJOEE.4.1.1-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents a nonlinear modeling of the PEMFC using Neural Network Auto-Regressive model with eXogenous inputs (NNARX) approach. The Multilayer Perception (MLP) network is applied to evaluate the structure of the NNARX model of PEMFC. The NNARX model structure is according to the Optimal Brain Surgeon (OBS) methodology to indicate the significant network structure. The validity and accuracy of NNARX model are tested by one step ahead relating output voltage to input current from measured experimental of PEMFC. The results show that the obtained nonlinear NNARX model based on OBS technique can efficiently approximate the dynamic mode of the PEMFC and model output and system measured output consistently. \",\"PeriodicalId\":13951,\"journal\":{\"name\":\"International Journal of Electrical Energy\",\"volume\":\"16 1\",\"pages\":\"1-5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Electrical Energy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18178/IJOEE.4.1.1-5\",\"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 Electrical Energy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18178/IJOEE.4.1.1-5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
NNARX Model of the PEMFC Used Neural Network Pruning Model Structure
The paper presents a nonlinear modeling of the PEMFC using Neural Network Auto-Regressive model with eXogenous inputs (NNARX) approach. The Multilayer Perception (MLP) network is applied to evaluate the structure of the NNARX model of PEMFC. The NNARX model structure is according to the Optimal Brain Surgeon (OBS) methodology to indicate the significant network structure. The validity and accuracy of NNARX model are tested by one step ahead relating output voltage to input current from measured experimental of PEMFC. The results show that the obtained nonlinear NNARX model based on OBS technique can efficiently approximate the dynamic mode of the PEMFC and model output and system measured output consistently.