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This study presents a hybrid approach combining experimental analysis, process simulation, and machine learning to optimize methane production from food waste and cow dung in anaerobic digestion. Key findings indicate that optimal conditions for methane yield include a temperature of 320 K and a hydraulic retention time of 15 days, with machine learning models like Support Vector Regression providing high predictive accuracy. The research emphasizes the importance of integrating various methodologies to enh

Author
siam.hithium
Language
EN

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