Enhancement of quality and quantity of woody biomass produced in forests using machine learning algorithms

W Peng, OK Sadaghiani - Biomass and Bioenergy, 2023 - Elsevier
Forest is considered a significant source of woody biomass production. Sustainable
production of wood, lower emittance of CO2 from burning, and lower amount of sulfur and …

An Analytical Review on the Utilization of Machine Learning in the Biomass Raw Materials, Their Evaluation, Storage, and Transportation

W Peng, OK Sadaghiani - Archives of Computational Methods in …, 2023 - Springer
The utilization of biomass, as an energy resources, is required four main steps of production,
pre-treatment, bio-refinery, and upgrading. Also, the production step of the biomass raw …

Low temperature carbonized mesoporous graphitic carbon for tetracycline adsorption: mechanistic insight and adaptive neuro-fuzzy inference system modeling

R Vinayagam, A Kar, G Murugesan… - Bioresource Technology …, 2023 - Elsevier
Tetracycline (TC) contamination is prevalent in aquatic systems due to its uncontrolled and
excessive use for medical, livestock, and veterinary purposes. Herein, we produced low …

[HTML][HTML] Prediction of energy content of biomass based on hybrid machine learning ensemble algorithm

UA Dodo, EC Ashigwuike, JN Emechebe, SI Abba - Energy Nexus, 2022 - Elsevier
In this study, three novel ensemble algorithms, namely, simple averaging, weighted
averaging, and meta-learning ensemble algorithms were employed to predict the higher …

[HTML][HTML] In-depth physico-chemical characterisation and estimation of the grid power potential of municipal solid wastes in Abuja city

UA Dodo, EC Ashigwuike - Energy Nexus, 2023 - Elsevier
Ineffective municipal solid waste (MSW) management is one of the major impediments to the
realisation of sustainable development goals by developing countries. Prudent waste …

A glass-box approach for predictive modeling based on experimental data for a waste biomass derived producer gas-powered dual-fuel engine

TT Le, P Sharma, HC Le, HS Le, SM Osman… - International Journal of …, 2024 - Elsevier
The utilization of waste biomass-derived producer gas in dual-fuel engines has attracted a
lot of interest as a sustainable energy option that encourages waste reduction as well as …

A blended ensemble model for biomass HHV prediction from ultimate analysis

N Pachauri, CW Ahn, TJ Choi - Fuel, 2024 - Elsevier
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 …

Toward sustainable crop residue management: A deep ensemble learning approach

SN Ferdous, X Li, K Sahoo, R Bergman - Bioresource Technology Reports, 2023 - Elsevier
For the existence of biorefineries, a consistent supply of sustainable crop residues is critical.
Crop residue removal may adversely affect the overall sustainability, ie, soil productivity and …

[HTML][HTML] Prognostic Metamodel Development for Waste-Derived Biogas-Powered Dual-Fuel Engines Using Modern Machine Learning with K-Cross Fold Validation

M Alruqi, HA Hanafi, P Sharma - Fermentation, 2023 - mdpi.com
Attention over greenhouse gas emissions has driven interest in cleaner energy sources
including alternative fuels. Waste-derived biogas, which is produced by the anaerobic …

[HTML][HTML] Comparative study of different training algorithms in backpropagation neural networks for generalized biomass higher heating value prediction

UA Dodo, MA Dodo, MA Husein, EC Ashigwuike… - Green Energy and …, 2024 - Elsevier
When selecting biomass feedstock for sustainable heat and electricity generation, higher
heating value (HHV) is an important consideration. Meanwhile, the laboratory procedures of …