Cellulosic biomass fermentation for biofuel production: Review of artificial intelligence approaches
Scarcity in fossil fuel reserves and their environmental impacts has forced the world towards
the production of clean and environment-friendly fuels called biofuels. This review focuses …
the production of clean and environment-friendly fuels called biofuels. This review focuses …
Advances in machine learning technology for sustainable biofuel production systems in lignocellulosic biorefineries
In view of the global climate change concerns, the society is approaching towards the
development of 'green'and renewable energies for sustainable future. The non-renewable …
development of 'green'and renewable energies for sustainable future. The non-renewable …
State-of-the-art and future directions of machine learning for biomass characterization and for sustainable biorefinery
Abstract Machine learning (ML) has emerged as a significant tool in the field of biorefinery,
offering the capability to analyze and predict complex processes with efficiency. This article …
offering the capability to analyze and predict complex processes with efficiency. This article …
Smart sustainable biorefineries for lignocellulosic biomass
Lignocellulosic biomass (LCB) is considered as a sustainable feedstock for a biorefinery to
generate biofuels and other bio-chemicals. However, commercialization is one of the …
generate biofuels and other bio-chemicals. However, commercialization is one of the …
[HTML][HTML] Ionic liquid-assisted bioconversion of lignocellulosic biomass for the development of value-added products
Lignocellulosic biomass is the most abundant inexpensive renewable source for obtaining
biofuels and bioproducts. One of the greatest problems faced in valorizing biomass arises …
biofuels and bioproducts. One of the greatest problems faced in valorizing biomass arises …
Designing a sustainable bioethanol supply chain network: A combination of machine learning and meta-heuristic algorithms
Bioethanol demands have increased during the last decade due to unexpected events
worldwide. It is among the renewable energy sources that are utilized to replace fossil-fuel …
worldwide. It is among the renewable energy sources that are utilized to replace fossil-fuel …
Selection of independent variables for crop yield prediction using artificial neural network models with remote sensing data
P Hara, M Piekutowska, G Niedbała - Land, 2021 - mdpi.com
Knowing the expected crop yield in the current growing season provides valuable
information for farmers, policy makers, and food processing plants. One of the main benefits …
information for farmers, policy makers, and food processing plants. One of the main benefits …
Natural melanin: current trends, and future approaches, with especial reference to microbial source
NEA El-Naggar, WEIA Saber - Polymers, 2022 - mdpi.com
Melanin is a universal natural dark polymeric pigment, arising in microorganisms, animals,
and plants. There is a couple of pieces of literature on melanin, each focusing on a different …
and plants. There is a couple of pieces of literature on melanin, each focusing on a different …
[HTML][HTML] An integrated machine learning and quantitative optimization method for designing sustainable bioethanol supply chain networks
Increasing demand for energy is pushing decision-makers in the Bioethanol Supply Chain
Network (BSCN) to adopt second-generation biomass feedstocks to meet sustainability …
Network (BSCN) to adopt second-generation biomass feedstocks to meet sustainability …
[HTML][HTML] A critical review of machine learning for lignocellulosic ethanol production via fermentation route
In this work, machine learning (ML) applications in lignocellulosic bioethanol production
were reviewed. First, the pretreatment-hydrolysis-fermentation route, the most commonly …
were reviewed. First, the pretreatment-hydrolysis-fermentation route, the most commonly …