Artificial neural network applied forecast on a parametric study of Calophyllum inophyllum methyl ester-diesel engine out responses

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• 作者：Charudatta M. Kshirsagar ^{cssn_ksagar@rediffmail.com} ; Ramanathan Anand ; ^{anandachu@nitt.edu}
• 关键词：Biodiesel-diesel blends ; Diesel engine ; Performance ; Emission ; Parametric study
• 刊名：Applied Energy
• 出版年：2017
• 出版时间：1 March 2017
• 年：2017
• 卷：189
• 期：Complete
• 页码：555-567
• 全文大小：1650 K
• 卷排序：189

文摘

Reduction in BSEC, CO, UBHC, soot and engine out O2 at high fuel injection pressure. ANN modelling of BTE, BSEC, EGT, CO, CO2, UBHC, NO, dry soot and engine out O2. Use of MSE, RMSE, R, R2, MAPE, MSRE, NSE and THEIL U2 metrics as evaluation criteria. The proposed ANN models map the engine out responses with better accuracy.