Assessing the mutual benefits of artificial intelligence (AI) and bioenergy systems, to promote efficient and sustainable energy production. By addressing issues with conventional bioenergy techniques, it highlights how AI is revolutionising optimisa...
Biogas yield in anaerobic digestion (AD) involves continuous and complex biological reactions. The traditional linear models failed to quantitatively assess the interactive effects of these factors on AD performance. To further explore the internal r...
Based on operational data collected over 1.5 years from four full-scale dry anaerobic digesters used for kitchen food waste treatment, this study adopted eight typical machine learning algorithms to distinguish the best biogas prediction model and to...
In this study, Desmodesmus pannonicus IITISM-DIX2, outperforming Chlorella sorokiniana IITISM-DIX3 in caffeine degradation, was used to develop an artificial neural network (ANN) model for predicting caffeine removal efficiency under varying pH, phot...
Environmental science and pollution research international
39638894
Waste-centred-bioenergy generation have been garnering interest over the years due to environmental impact presented by fossil fuels. Waste generation is an unavoidable consequence of urbanization and population growth. Sustainable waste management t...
Anaerobic digestion (AD), which relies on a complex microbial consortium for efficient biogas generation, is a promising avenue for renewable energy production and organic waste treatment. However, understanding and optimising AD processes are challe...
The growing demand for efficient waste management solutions and renewable energy sources has driven research into predicting biogas production at wastewater treatment plants. This study outlines a methodology starting with data collection from a full...
The lignocellulosic biorefinery involves pretreatment, enzymatic hydrolysis, mixed sugar fermentation, and optional anaerobic digestion. This pipeline could be effectively implemented through machine learning (ML)-guided process optimization and stra...
Nonlinear autoregressive exogenous (NARX) neural network models were used to forecast the time-series profiles of anaerobic digestion-elutriated phase treatment (ADEPT). Experimental data from the operation of the pilot plant and lab-scale reactor we...
The global production of biodiesel in 2023 amounted to 34 billion liters because compression ignition engines need environmentally friendly fuel alternatives. The research investigates Annona biodiesel in combination with machine learning (ML) and ST...