Application of gene expression programming, artificial neural network and multilinear regression in predicting hydrochar physicochemical properties
Abstract
Globally, the provision of energy is becoming an absolute necessity. Biomass resources are abundant and have been described as a potential alternative source of energy. However, it is important to assess the fuel characteristics of the various available biomass sources. Soft computing techniques are presented in this study to predict the mass yield (MY), energy yield (EY), and higher heating value (HHV) of hydrothermally carbonized biomass using...
Paper Details
Title
Application of gene expression programming, artificial neural network and multilinear regression in predicting hydrochar physicochemical properties
Published Date
Nov 27, 2020
Volume
7
Issue
1
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