Multifunctional applications of bamboo crop beyond environmental management: an Indian prospective

R Rathour, H Kumar, K Prasad, P Anerao… - …, 2022 - Taylor & Francis
Increasing population, industrialization, and economic growth cause several adverse
impacts on the existing environment and living being. Therefore, rising pollutants load and …

[HTML][HTML] Progress in thermodynamic simulation and system optimization of pyrolysis and gasification of biomass

Y Zhang, Y Ji, H Qian - Green Chemical Engineering, 2021 - Elsevier
Due to the shortage of fossil energy, biomass has a potential to be a very promising
alternative source. Unfortunately, a large part of biomass resources worldwide causes …

[HTML][HTML] Predictability of higher heating value of biomass feedstocks via proximate and ultimate analyses–A comprehensive study of artificial neural network …

F Güleç, D Pekaslan, O Williams, E Lester - Fuel, 2022 - Elsevier
Higher heating value (HHV) is a key characteristic for the assessment and selection of
biomass feedstocks as a fuel source. The HHV is usually measured using an adiabatic …

Predicting streamflow in Peninsular Malaysia using support vector machine and deep learning algorithms

Y Essam, YF Huang, JL Ng, AH Birima, AN Ahmed… - Scientific Reports, 2022 - nature.com
Floods and droughts are environmental phenomena that occur in Peninsular Malaysia due
to extreme values of streamflow (SF). Due to this, the study of SF prediction is highly …

Machine learning application to predict the Mechanical properties of Glass Fiber mortar

G Nakkeeran, L Krishnaraj, A Bahrami… - … in Engineering Software, 2023 - Elsevier
In this study, the mechanical properties of glass fiber mortars have been predicted using
machine learning tools, Response Surface Methodology (RSM), and Artificial Neural …

[HTML][HTML] RSM and ANN modelling of the mechanical properties of self-compacting concrete with silica fume and plastic waste as partial constituent replacement

OM Ofuyatan, OB Agbawhe, DO Omole, CA Igwegbe… - Cleaner Materials, 2022 - Elsevier
Abstract In this study, Response Surface Methodology (RSM) and Artificial Neural Networks
(ANN) was used to predict the mechanical properties of self-compacting concrete (SCC) with …

Machine learning models for biomass energy content prediction: a correlation-based optimal feature selection approach

UA Dodo, EC Ashigwuike, SI Abba - Bioresource Technology Reports, 2022 - Elsevier
In this study, a multilinear regression (MLR) and three machine learning techniques, ie, an
adaptive neuro-fuzzy inference system (ANFIS), an artificial neural network (ANN), and a …

Machine learning approach for the prediction of biomass pyrolysis kinetics from preliminary analysis

HK Balsora, S Kartik, V Dua, JB Joshi, G Kataria… - Journal of …, 2022 - Elsevier
The pyrolytic behavior of lignocellulosic biomass is highly complex, and its kinetic behavior
varies with operating conditions and the type of biomass. To reduce timescales, cost and …

Neurocomputing modelling of hydrochemical and physical properties of groundwater coupled with spatial clustering, GIS, and statistical techniques

M Benaafi, MA Yassin, AG Usman, SI Abba - Sustainability, 2022 - mdpi.com
Groundwater (GW) is a critical freshwater resource for billions of individuals worldwide.
Rapid anthropogenic exploitation has increasingly deteriorated GW quality and quantity …

[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 …