Prediction of critical properties of biodiesel fuels from FAMEs compositions using intelligent genetic algorithm-based back propagation neural network

Numerical study of soot particles from low temperature combustion of engine fueled with diesel fuel and unsaturation biodiesel fuels

(2018) Feiyang Zhao et al.   APPLIED ENERGY

Effects of fatty acid methyl esters proportion on combustion and emission characteristics of a biodiesel fueled marine diesel engine

(2018) Zhiqing Zhang et al.   ENERGY CONVERSION AND MANAGEMENT

Prediction of density and kinematic viscosity of biodiesel by artificial neural networks

(2017) Ceyla Özgür et al.   Energy Sources Part A-Recovery Utilization and Environmental Effects

Fatty acid based prediction models for biodiesel properties incorporating compositional uncertainty

(2017) Carla Caldeira et al.   FUEL

Dependence of cold filter plugging point on saturated fatty acid profile of biodiesel blends derived from different feedstocks

(2017) Min-Hao Yuan et al.   FUEL

Exact estimation of biodiesel cetane number (CN) from its fatty acid methyl esters (FAMEs) profile using partial least square (PLS) adapted by artificial neural network (ANN)

(2016) Soleiman Hosseinpour et al.   ENERGY CONVERSION AND MANAGEMENT

Effects of fatty acid methyl esters proportion on combustion and emission characteristics of a biodiesel fueled diesel engine

(2016) Jiaqiang E et al.   ENERGY CONVERSION AND MANAGEMENT

Ignition temperature and activation energy of power coal blends predicted with back-propagation neural network models

(2016) Jun Cheng et al.   FUEL

Direct interval forecasting of wind speed using radial basis function neural networks in a multi-objective optimization framework

(2016) Chi Zhang et al.   NEUROCOMPUTING

Prediction of selected biodiesel fuel properties using artificial neural network

(2015) Solomon O. Giwa et al.   Frontiers in Energy

Integration of fuzzy neural network and artificial immune system-based back-propagation neural network for sales forecasting using qualitative and quantitative data

(2014) R. J. Kuo et al.   JOURNAL OF INTELLIGENT MANUFACTURING

Neural network prediction of biodiesel kinematic viscosity at 313K

(2013) Xiangzan Meng et al.   FUEL

Prediction of biodiesel fuel properties from fatty acid alkyl ester

(2013) In Kwon Hong et al.   JOURNAL OF INDUSTRIAL AND ENGINEERING CHEMISTRY

Fuel Properties of Highly Polyunsaturated Fatty Acid Methyl Esters. Prediction of Fuel Properties of Algal Biodiesel

(2012) Gerhard Knothe   ENERGY & FUELS

Prediction of the cetane number of biodiesel using artificial neural networks and multiple linear regression

(2012) Ramón Piloto-Rodríguez et al.   ENERGY CONVERSION AND MANAGEMENT

A statistical investigation of biodiesel physical and chemical properties, and their correlation with the degree of unsaturation

(2012) Evangelos G. Giakoumis   RENEWABLE ENERGY

Multiple response optimization of vegetable oils fatty acid composition to improve biodiesel physical properties

(2011) S. Pinzi et al.   BIORESOURCE TECHNOLOGY

Predicting cetane number, kinematic viscosity, density and higher heating value of biodiesel from its fatty acid methyl ester composition

(2011) Luis Felipe Ramírez-Verduzco et al.   FUEL

Parametric optimization design for supercritical CO2 power cycle using genetic algorithm and artificial neural network

(2009) Jiangfeng Wang et al.   APPLIED ENERGY

Theoretical modeling of iodine value and saponification value of biodiesel fuels from their fatty acid composition

(2009) A. Gopinath et al.   RENEWABLE ENERGY

Influence of fatty acid composition of raw materials on biodiesel properties

(2008) María Jesús Ramos et al.   BIORESOURCE TECHNOLOGY