A comparison of machine learning algorithms for estimation of higher heating values of biomass and fossil fuels from ultimate analysis

Classification of solid fuels with machine learning

(2020) Furkan Elmaz et al.   FUEL

Machine learning based modelling for lower heating value prediction of municipal solid waste

(2020) Cansu Birgen et al.   FUEL

Bioenergy technologies, uses, market and future trends with Austria as a case study

(2020) A. Anca-Couce et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Experimental study on erosion behavior of fracturing pipeline involving tensile stress and erosion prediction using random forest regression

(2020) Siqi Yang et al.   Journal of Natural Gas Science and Engineering

Biomass higher heating value prediction from ultimate analysis using multiple regression and genetic programming

(2019) Imane Boumanchar et al.   Biomass Conversion and Biorefinery

Evaluating explorative prediction power of machine learning algorithms for materials discovery using k-fold forward cross-validation

(2019) Zheng Xiong et al.   COMPUTATIONAL MATERIALS SCIENCE

A comprehensive study on estimating higher heating value of biomass from proximate and ultimate analysis with machine learning approaches

(2019) Jiangkuan Xing et al.   ENERGY

Estimation of biomass higher heating value (HHV) based on the proximate analysis: Smart modeling and correlation

(2019) Amir Dashti et al.   FUEL

A heating value estimation of refuse derived fuel using the genetic programming model

(2019) Kemal Özkan et al.   WASTE MANAGEMENT

Prediction of higher heating values of biochar from proximate and ultimate analysis

(2019) Cheng Qian et al.   FUEL

Biomass higher heating value (HHV) modeling on the basis of proximate analysis using iterative network-based fuzzy partial least squares coupled with principle component analysis (PCA-INFPLS)

(2018) Soleiman Hosseinpour et al.   FUEL

Statistical and Machine Learning forecasting methods: Concerns and ways forward

(2018) Spyros Makridakis et al.   PLoS One

Prediction of elemental composition of coal using proximate analysis

(2017) Lan Yi et al.   FUEL

Multiple predicting K-fold cross-validation for model selection

(2017) Yoonsuh Jung   JOURNAL OF NONPARAMETRIC STATISTICS

Parametric methods for comparing the performance of two classification algorithms evaluated by k-fold cross validation on multiple data sets

(2017) Tzu-Tsung Wong   PATTERN RECOGNITION

Effects of Oxygen Content of Fuels on Combustion and Emissions of Diesel Engines

(2016) Haiwen Song et al.   Energies

Calculation of higher heating values of fatty acids

(2016) Ayhan Demirbas   Energy Sources Part A-Recovery Utilization and Environmental Effects

Characterization, thermochemical conversion studies, and heating value modeling of municipal solid waste

(2016) Honghong Shi et al.   WASTE MANAGEMENT

Predictive modeling of groundwater nitrate pollution using Random Forest and multisource variables related to intrinsic and specific vulnerability: A case study in an agricultural setting (Southern Spain)

(2014) Victor Rodriguez-Galiano et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Model detection for functional polynomial regression

(2013) Tao Zhang et al.   COMPUTATIONAL STATISTICS & DATA ANALYSIS

Estimation of higher heating value of biomass from proximate analysis: A new approach

(2012) Daya Ram Nhuchhen et al.   FUEL

Optimization of an artificial neural network dedicated to the multivariate forecasting of daily global radiation

(2010) Cyril Voyant et al.   ENERGY

Prediction of higher heating values of biomass from proximate and ultimate analyses

(2010) Chun-Yang Yin   FUEL

An overview of the chemical composition of biomass

(2009) Stanislav V. Vassilev et al.   FUEL

Development of a new proximate analysis based correlation to predict calorific value of coal

(2008) A MAJUMDER et al.   FUEL

Comparison of decision tree methods for finding active objects

(2007) Yongheng Zhao et al.   ADVANCES IN SPACE RESEARCH

Adjusted -type measures for Tweedie models

(2007) Lila Ricci et al.   COMPUTATIONAL STATISTICS & DATA ANALYSIS