Predicting the adsorption of ammonia nitrogen by biochar in water bodies using machine learning strategies: model optimization and analysis of key characteristic variables DOI

Xie Guixian,

Chi Zhu,

Chen Li

et al.

Environmental Research, Journal Year: 2024, Volume and Issue: unknown, P. 120618 - 120618

Published: Dec. 1, 2024

Language: Английский

Co-pyrolysis of biomass and plastic wastes and application of machine learning for modelling of the process: A comprehensive review DOI

Deepak Bhushan,

Sanjeevani Hooda,

Prasenjit Mondal

et al.

Journal of the Energy Institute, Journal Year: 2025, Volume and Issue: 119, P. 101973 - 101973

Published: Jan. 5, 2025

Language: Английский

Citations

2
Machine learning prediction of bio-oil production from the pyrolysis of lignocellulosic biomass: Recent advances and future perspectives DOI Creative Commons
Hyojin Lee, Il-Ho Choi, Kyung-Ran Hwang

et al.

Journal of Analytical and Applied Pyrolysis, Journal Year: 2024, Volume and Issue: 179, P. 106486 - 106486

Published: March 30, 2024

Bio-oil produced through pyrolysis of lignocellulosic biomass has recently received significant attention due to its possible uses as a second-generation biofuel. The yield and characteristics bio-oil are affected by reaction conditions the type feedstock that is used. Recently, machine learning (ML) techniques have been widely employed forecast performance bi-oil. In this study, comprehensive review ML research on carried out. Regression methods were most frequently build prediction models top five for random forest, artificial neural network, gradient boosting, support vector regression, linear regression. results developed quite consistent with experiment results. However, studies data had limitations such used restricted data, extraction features using their own knowledge, limited algorithms. We highlighted challenges potential cutting-edge in production.

Language: Английский

Citations

10
Machine learning to predict the production of bio-oil, biogas, and biochar by pyrolysis of biomass: a review DOI
Kapil Khandelwal, Sonil Nanda, Ajay K. Dalai

et al.

Environmental Chemistry Letters, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 5, 2024

Language: Английский

Citations

10
Artificial intelligence-driven prediction models for the cultivation of Chlorella vulgaris FSP-E in food waste culture medium: A comparative analysis and validation of models DOI
Adityas Agung Ramandani, Jun Wei Roy Chong, Sirasit Srinuanpan

et al.

Algal Research, Journal Year: 2025, Volume and Issue: unknown, P. 103935 - 103935

Published: Jan. 1, 2025

Language: Английский

Citations

1
Microwave-assisted In-situ catalytic co-pyrolysis of polypropylene and polystyrene mixtures: Response surface methodology analysis using machine learning DOI

Dinesh Kamireddi,

Avinash Terapalli,

V. Sridevi

et al.

Journal of Analytical and Applied Pyrolysis, Journal Year: 2023, Volume and Issue: 172, P. 105984 - 105984

Published: April 28, 2023

Language: Английский

Citations

19
From Microalgae to Bioenergy: Recent Advances in Biochemical Conversion Processes DOI Creative Commons
Sheetal Kishor Parakh,

Zinong Tian,

Jonathan Zhi En Wong

et al.

Fermentation, Journal Year: 2023, Volume and Issue: 9(6), P. 529 - 529

Published: May 29, 2023

Concerns about rising energy demand, fossil fuel depletion, and global warming have increased interest in developing utilizing alternate renewable sources. Among the available resources, microalgae biomass, a third-generation feedstock, is promising for production due to its rich biochemical composition, metabolic elasticity, ability produce numerous bioenergy products, including biomethane, biohydrogen, bioethanol. However, true potential of biomass future economy yet be realized. This review provides comprehensive overview various conversion processes (anaerobic digestion, direct biophotolysis, indirect photo fermentation, dark microalgae-catalyzed traditional alcoholic fermentation by ethanologenic microorganisms) that could adapted transform into different products. Recent advances are compiled critically analyzed, their limitations terms process viability, efficacy, scalability, economic environmental sustainability highlighted. Based on current research stage technological development, biomethane from anaerobic digestion bioethanol identified as methods commercialization microalgae-based bioenergy. significant challenges these technologies’ remain, high costs low recovery efficiency. Future should focus reducing costs, an integrated biorefinery approach, effectively artificial intelligence tools optimization scale-up solve accelerate development

Language: Английский

Citations

18
Sustainable hydrogen production via microalgae: Technological advancements, economic indicators, environmental aspects, challenges, and policy implications DOI
Hafiz Muhammad Uzair Ayub, Muhammad Nizami, Muhammad Abdul Qyyum

et al.

Environmental Research, Journal Year: 2023, Volume and Issue: 244, P. 117815 - 117815

Published: Dec. 3, 2023

Language: Английский

Citations

18
Torrefied biomass quality prediction and optimization using machine learning algorithms DOI Creative Commons
Muhammad Naveed,

Jawad Gul,

Muhammad Nouman Aslam Khan

et al.

Chemical Engineering Journal Advances, Journal Year: 2024, Volume and Issue: 19, P. 100620 - 100620

Published: June 26, 2024

Torrefied biomass is a vital green energy source with applications in circular economies, addressing agricultural residue and rising demands. In this study, ML models were used to predict durability (%) mass loss (%). Firstly, data was collected preprocessed, its distribution correlation analyzed. Gaussian Process Regression (GPR) Ensemble Learning Trees (ELT) then trained tested on 80 % 20 of the data, respectively. Both machine learning underwent optimization through Genetic Algorithm (GA) Particle Swarm Optimization (PSO) for feature selection hyperparameter tuning. GPR-PSO demonstrates excellent accuracy predicting (%), achieving training R2 score 0.9469 an RMSE value 0.0785. GPR-GA exhibits exceptional performance 1 9.7373e-05. The temperature duration during torrefaction are crucial variables that line conclusions drawn from previous studies. GPR ELT effectively optimize torrefied quality, leading enhanced density, mechanical properties, grindability, storage stability. Additionally, they contribute sustainable agriculture by reducing carbon emissions, improving cost-effectiveness, aiding design development pelletizers. This not only increases density grindability but also enhances nutrient delivery efficiency, water retention, reduces footprint. Consequently, these outcomes support biodiversity promote agricultural, ecosystem, environmental practices.

Language: Английский

Citations

8
Aging prediction in single based propellants using hybrid strategy of machine learning and genetic algorithm DOI

Faizan Khalid,

Muhammad Nouman Aslam,

Muhammad Abdaal Ghani

et al.

Chemometrics and Intelligent Laboratory Systems, Journal Year: 2024, Volume and Issue: 245, P. 105058 - 105058

Published: Jan. 2, 2024

Language: Английский

Citations

6
A data-driven multi-objective optimization approach for enhanced methanol yield and exergy loss minimization in direct hydrogenation of CO2 DOI

Abdul Samad,

Husnain Saghir,

Abdul Musawwir

et al.

Applied Thermal Engineering, Journal Year: 2024, Volume and Issue: 251, P. 123517 - 123517

Published: May 31, 2024

Language: Английский

Citations

6