In order to accurately anticipate the proficiency of downdraft biomass gasification linked with
a water–gas shift unit to produce biohydrogen, a model based on an artificial neural network …

Energy generation from renewable and carbon-neutral biomass is significant in the context
of a sustainable energy framework. Hydrogen can be conveniently extracted from biomass …

In this study, a robust model using bootstrapped aggregated neural network (BANN) was
developed for optimising operating conditions of a two-stage gasification for high carbon …

Prediction of clean hydrogen production via biomass gasification by supervised machine
learning algorithms was studied. Lab-scale gasification studies were performed in a steel …

This paper explores the construction and validation of an artificial neural network (ANN)
model to accurately and efficiently predict the performance of a downdraft biomass …

Quality syngas production with higher moles of hydrogen and methane are the primary
objective of gasification process which is dependent upon the process parameters and …

A two-stage gasification has been proven as an effective and robust approach for converting
low-valued and/or highly heterogeneous materials ie waste, into hydrogen and/or syngas …

Alternative renewable fuels like biomass have the potential to be considered for electricity
generation by replacing the utilization of fossil fuels and reducing the greenhouse gas …

In the context of Industry 4.0, hydrogen gas is becoming more significant to energy
feedstocks in the world. The current work researches a novel artificial smart model for …

A significant driver of global warming is fast growth in greenhouse gas (GHG) generated by
energy-producing areas. Converting biomass into useful products, chemical looping …