DOI:​10.1016/J.ENERGY.2015.11.008
Corpus ID: 110177193
The use of ELM-WT (extreme learning machine with wavelet transform algorithm) to predict exergetic performance of a DI diesel engine running on diesel/biodiesel blends containing polymer waste
M. Aghbashlo, Shahaboddin Shamshirband, +2 authorsYaser Nabavi Larimi
Published 2016
Engineering
Energy
In this study, a novel method based on Extreme Learning Machine with wavelet transform algorithm (ELM-WT) was designed and adapted to estimate the exergetic performance of a DI diesel engine. The… Expand
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2015
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Exergy analysis of engines fuelled with biodiesel from high oleic soybeans based on experimental values
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Environmental Science
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This study dealt with energy and exergy analyses of a John Deere 4045T diesel engine run with no. 2 diesel fuel, Soybean oil Methyl Ester (SME) and High-Oleic soybean oil Methyl Ester (HOME) at 1400… Expand
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Monthly river flow forecasting using artificial neural network and support vector regression models coupled with wavelet transform
A. Kalteh
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This study investigates the relative accuracy of artificial neural network and support vector regression models coupled with wavelet transform in monthly river flow forecasting, and indicates that regular SVR models perform slightly better than regular ANN models. Expand
141 Citations
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