Ultimate_Analysis - Mendeley Data The database includes the datasets and source codes to analyze the performance consistency of the biomass HHV These datasets are stored in tabular on an excel workbook
A blended ensemble model for biomass HHV prediction from ultimate analysis This work proposes a new blended stacked ensemble machine-learning model (BEM) to predict biomass’s higher heating value (HHV) from the ultimate analysis Gorilla troop optimization (GTO) is utilized to estimate the hyperparameter values of BEM, leading to GBEM
Ultimate_Analysis - Roosevelt University The database includes the datasets and source codes to analyze the performance consistency of the biomass HHV These datasets are stored in tabular on an excel workbook The source codes are the biomass HHV machine learning model through the MATLAB Objected Orient Program (OOP)
Biomass higher heating value prediction from ultimate analysis using . . . For this reason, several researches have been interested to develop mathematical models for the prediction of HHV from fundamental composition The purpose of this study is to develop new correlations to determine the biomass HHV from ultimate analysis As a result, two models were elaborated
Estimation of higher heating values (HHVs) of biomass fuels based on . . . Chemical constituents or elements are essential properties in biomass applications, which would be costly and labor-intensive to experimentally estimate them One of the criteria to evaluate the energy of biomass from an economic perspective is the higher heating value (HHV)
Basic information and high heat value of biomass raw materials This dataset is not only applicable to machine learning models for predicting biochar yield or HHV but also useful for analyzing how input features (such as composition and temperature) affect the output