Biomethane production from sugarcane vinasse in a circular economy: Developments and innovations

JC de Carvalho, LP de Souza Vandenberghe… - Fermentation, 2023 - mdpi.com
Sugarcane ethanol production generates about 360 billion liters of vinasse, a liquid effluent
with an average chemical oxygen demand of 46,000 mg/L. Vinasse still contains about 11 …

[HTML][HTML] Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network

F Almomani - Fuel, 2020 - Elsevier
The present study evaluates the effect of co-digestion of agricultural solid wastes (ASWs),
cow manure (CM), and the application of chemical pre-treatment with NaHCO 3 on the …

Effect of biomass co-digestion and application of artificial intelligence in biogas production: a review

MO Fajobi, OA Lasode, AA Adeleke… - Energy Sources, Part …, 2022 - Taylor & Francis
Energy is an essential bedrock, which plays a high impact role in the running of domestic
and industrial activities. Most energy used for these activities is majorly from conventional …

Artificial neural network model to predict behavior of biogas production curve from mixed lignocellulosic co-substrates

MD Ghatak, A Ghatak - Fuel, 2018 - Elsevier
Depletion of fossil fuels and increase in global pollution at an alarming rate has encouraged
the researchers to look for environmental friendly and cost effective alternative sources of …

Application of artificial neural network and kinetic modeling for the prediction of biogas and methane production in anaerobic digestion of several organic wastes

NE Mougari, JF Largeau, N Himrane… - … Journal of Green …, 2021 - Taylor & Francis
In the current study, artificial neural network (ANN) and modified Gompertz equation (MG)
were applied to develop integrated based models for the prediction of cumulative biogas …

[HTML][HTML] Prediction the performance of multistage moving bed biological process using artificial neural network (ANN)

F Almomani - Science of The Total Environment, 2020 - Elsevier
Complexity, uncertainty, and high dynamic nature of nutrient removal through biological
processes (BPs) makes it difficult to model and control these processes, forcing designers to …

Artificial neural network (ANN) modelling for biogas production in pre-commercialized integrated anaerobic-aerobic bioreactors (IAAB)

WY Chen, YJ Chan, JW Lim, CS Liew, M Mohamad… - Water, 2022 - mdpi.com
The use of integrated anaerobic-aerobic bioreactor (IAAB) to treat the Palm Oil Mill Effluent
(POME) showed promising results, which successfully overcome the limitation of a large …

[HTML][HTML] Forecast of the outbreak of COVID-19 using artificial neural network: Case study Qatar, Spain, and Italy

M Shawaqfah, F Almomani - Results in Physics, 2021 - Elsevier
The present study illustrates the outbreak prediction and analysis on the growth and
expansion of the COVID-19 pandemic using artificial neural network (ANN). The first wave of …

[HTML][HTML] Solar nanophotocatalytic pretreatment of seawater: process optimization and performance evaluation using response surface methodology and genetic …

VM Joy, S Feroz, S Dutta - Applied Water Science, 2021 - Springer
In reverse osmosis seawater treatment process, membrane fouling can be mitigated by
degrading organic pollutants present in the feed seawater. The present study evaluates the …

Machine learning applications in biofuels' life cycle: Soil, feedstock, production, consumption, and emissions

I Ahmad, A Sana, M Kano, II Cheema, BC Menezes… - Energies, 2021 - mdpi.com
Machine Learning (ML) is one of the major driving forces behind the fourth industrial
revolution. This study reviews the ML applications in the life cycle stages of biofuels, ie, soil …