Optimization and prediction of biogas yield from pretreated Ulva Intestinalis Linnaeus applying statistical-based regression approach and machine learning algorithms

Aigbe, Uyiosa Osagie; Ukhurebor, Kingsley Eghonghon; Osibote, Adelaja Otolorin; Hassaan, Mohamed A.; El Nemr, Ahmed

doi:10.1016/j.renene.2024.121347

Renewable Energy

2024

DOI: 10.1016/j.renene.2024.121347

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Optimization and prediction of biogas yield from pretreated Ulva Intestinalis Linnaeus applying statistical-based regression approach and machine learning algorithms

Uyiosa Osagie Aigbe,

Kingsley Eghonghon Ukhurebor,

Adelaja Otolorin Osibote

et al.

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2024

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Cited by 2 publications

References 71 publications

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Ternary system approach in separation and purification of biodiesel fuel: An organised review

Adama,

Anani,

Ukhurebor

et al. 2024

Journal of Molecular Liquids

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Ternary system approach in separation and purification of biodiesel fuel: An organised review

Adama,

Anani,

Ukhurebor

et al. 2024

Journal of Molecular Liquids

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Fuzzy Neural Network Applications in Biomass Gasification and Pyrolysis for Biofuel Production: A Review

Bukhtoyarov,

Tynchenko,

Bashmur

et al. 2024

Energies

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The increasing demand for sustainable energy has spurred interest in biofuels as a renewable alternative to fossil fuels. Biomass gasification and pyrolysis are two prominent thermochemical conversion processes for biofuel production. While these processes are effective, they are often influenced by complex, nonlinear, and uncertain factors, making optimization and prediction challenging. This study highlights the application of fuzzy neural networks (FNNs)—a hybrid approach that integrates the strengths of fuzzy logic and neural networks—as a novel tool to address these challenges. Unlike traditional optimization methods, FNNs offer enhanced adaptability and accuracy in modeling nonlinear systems, making them uniquely suited for biomass conversion processes. This review not only highlights the ability of FNNs to optimize and predict the performance of gasification and pyrolysis processes but also identifies their role in advancing decision-making frameworks. Key challenges, benefits, and future research opportunities are also explored, showcasing the transformative potential of FNNs in biofuel production.

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Optimization and prediction of biogas yield from pretreated Ulva Intestinalis Linnaeus applying statistical-based regression approach and machine learning algorithms

Cited by 2 publications

References 71 publications

Ternary system approach in separation and purification of biodiesel fuel: An organised review

Ternary system approach in separation and purification of biodiesel fuel: An organised review

Fuzzy Neural Network Applications in Biomass Gasification and Pyrolysis for Biofuel Production: A Review

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