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Modeling and optimization of biogas production on saw dust and other co-substrates using Artificial Neural network and Genetic Algorithm

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Cited by:

  1. Damilola Elizabeth Babatunde & Ambrose Anozie & James Omoleye, 2020. "Artificial Neural Network and its Applications in the Energy Sector An Overview," International Journal of Energy Economics and Policy, Econjournals, vol. 10(2), pages 250-264.
  2. Olatunji, Kehinde O. & Ahmed, Noor A. & Madyira, Daniel M. & Adebayo, Ademola O. & Ogunkunle, Oyetola & Adeleke, Oluwatobi, 2022. "Performance evaluation of ANFIS and RSM modeling in predicting biogas and methane yields from Arachis hypogea shells pretreated with size reduction," Renewable Energy, Elsevier, vol. 189(C), pages 288-303.
  3. Wong, Pak Kin & Wong, Ka In & Vong, Chi Man & Cheung, Chun Shun, 2015. "Modeling and optimization of biodiesel engine performance using kernel-based extreme learning machine and cuckoo search," Renewable Energy, Elsevier, vol. 74(C), pages 640-647.
  4. Postawa, Karol & Szczygieł, Jerzy & Kułażyński, Marek, 2020. "A comprehensive comparison of ODE solvers for biochemical problems," Renewable Energy, Elsevier, vol. 156(C), pages 624-633.
  5. Abdel daiem, Mahmoud M. & Hatata, Ahmed & Galal, Osama H. & Said, Noha & Ahmed, Dalia, 2021. "Prediction of biogas production from anaerobic co-digestion of waste activated sludge and wheat straw using two-dimensional mathematical models and an artificial neural network," Renewable Energy, Elsevier, vol. 178(C), pages 226-240.
  6. Pomeroy, Brett & Grilc, Miha & Likozar, Blaž, 2022. "Artificial neural networks for bio-based chemical production or biorefining: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
  7. Maghanaki, M. Mohammadi & Ghobadian, B. & Najafi, G. & Galogah, R. Janzadeh, 2013. "Potential of biogas production in Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 702-714.
  8. Iftikhar Ahmad & Adil Sana & Manabu Kano & Izzat Iqbal Cheema & Brenno C. Menezes & Junaid Shahzad & Zahid Ullah & Muzammil Khan & Asad Habib, 2021. "Machine Learning Applications in Biofuels’ Life Cycle: Soil, Feedstock, Production, Consumption, and Emissions," Energies, MDPI, vol. 14(16), pages 1-27, August.
  9. Kucharska, Karolina & Hołowacz, Iwona & Konopacka-Łyskawa, Donata & Rybarczyk, Piotr & Kamiński, Marian, 2018. "Key issues in modeling and optimization of lignocellulosic biomass fermentative conversion to gaseous biofuels," Renewable Energy, Elsevier, vol. 129(PA), pages 384-408.
  10. Grahovac, Jovana & Jokić, Aleksandar & Dodić, Jelena & Vučurović, Damjan & Dodić, Siniša, 2016. "Modelling and prediction of bioethanol production from intermediates and byproduct of sugar beet processing using neural networks," Renewable Energy, Elsevier, vol. 85(C), pages 953-958.
  11. KeChrist Obileke & Golden Makaka & Nwabunwanne Nwokolo, 2022. "Efficient Methane Production from Anaerobic Digestion of Cow Dung: An Optimization Approach," Challenges, MDPI, vol. 13(2), pages 1-11, October.
  12. Hanniel Ferreira Sarmento de Freitas & José Eduardo Olivo & Cid Marcos Gonçalves Andrade, 2017. "Optimization of Bioethanol In Silico Production Process in a Fed-Batch Bioreactor Using Non-Linear Model Predictive Control and Evolutionary Computation Techniques," Energies, MDPI, vol. 10(11), pages 1-23, November.
  13. Abdel daiem, Mahmoud M. & Hatata, Ahmed & Said, Noha, 2022. "Modeling and optimization of semi-continuous anaerobic co-digestion of activated sludge and wheat straw using Nonlinear Autoregressive Exogenous neural network and seagull algorithm," Energy, Elsevier, vol. 241(C).
  14. Soltanali, Hamzeh & Nikkhah, Amin & Rohani, Abbas, 2017. "Energy audit of Iranian kiwifruit production using intelligent systems," Energy, Elsevier, vol. 139(C), pages 646-654.
  15. Chinese, D. & Patrizio, P. & Nardin, G., 2014. "Effects of changes in Italian bioenergy promotion schemes for agricultural biogas projects: Insights from a regional optimization model," Energy Policy, Elsevier, vol. 75(C), pages 189-205.
  16. Djatkov, Djordje & Effenberger, Mathias & Martinov, Milan, 2014. "Method for assessing and improving the efficiency of agricultural biogas plants based on fuzzy logic and expert systems," Applied Energy, Elsevier, vol. 134(C), pages 163-175.
  17. Krystel K. Castillo-Villar, 2014. "Metaheuristic Algorithms Applied to Bioenergy Supply Chain Problems: Theory, Review, Challenges, and Future," Energies, MDPI, vol. 7(11), pages 1-33, November.
  18. Leila Ezzatzadegan & Rubiyah Yusof & Noor Azian Morad & Parvaneh Shabanzadeh & Nur Syuhana Muda & Tohid N. Borhani, 2021. "Experimental and Artificial Intelligence Modelling Study of Oil Palm Trunk Sap Fermentation," Energies, MDPI, vol. 14(8), pages 1-22, April.
  19. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.
  20. Willeghems, Gwen & Buysse, Jeroen, 2016. "Changing old habits: The case of feeding patterns in anaerobic digesters," Renewable Energy, Elsevier, vol. 92(C), pages 212-221.
  21. Sakiewicz, P. & Piotrowski, K. & Ober, J. & Karwot, J., 2020. "Innovative artificial neural network approach for integrated biogas – wastewater treatment system modelling: Effect of plant operating parameters on process intensification," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
  22. Kowalczyk-Juśko, Alina & Pochwatka, Patrycja & Zaborowicz, Maciej & Czekała, Wojciech & Mazurkiewicz, Jakub & Mazur, Andrzej & Janczak, Damian & Marczuk, Andrzej & Dach, Jacek, 2020. "Energy value estimation of silages for substrate in biogas plants using an artificial neural network," Energy, Elsevier, vol. 202(C).
  23. Małgorzata Smuga-Kogut & Tomasz Kogut & Roksana Markiewicz & Adam Słowik, 2021. "Use of Machine Learning Methods for Predicting Amount of Bioethanol Obtained from Lignocellulosic Biomass with the Use of Ionic Liquids for Pretreatment," Energies, MDPI, vol. 14(1), pages 1-16, January.
  24. Elahi, Ehsan & Zhang, Zhixin & Khalid, Zainab & Xu, Haiyun, 2022. "Application of an artificial neural network to optimise energy inputs: An energy- and cost-saving strategy for commercial poultry farms," Energy, Elsevier, vol. 244(PB).
  25. Chaves, Gustavo T. & Teles, Felipe & Balbo, Antonio R. & dos Reis, Célia A. & Florentino, Helenice de Oliveira, 2024. "Mathematical modelling of biodigestion in an Indian biodigester and its stability analysis via Lyapunov technique," Renewable Energy, Elsevier, vol. 226(C).
  26. Betiku, Eriola & Okunsolawo, Samuel S. & Ajala, Sheriff O. & Odedele, Olatunde S., 2015. "Performance evaluation of artificial neural network coupled with generic algorithm and response surface methodology in modeling and optimization of biodiesel production process parameters from shea tr," Renewable Energy, Elsevier, vol. 76(C), pages 408-417.
  27. Patrizio, P. & Leduc, S. & Chinese, D. & Dotzauer, E. & Kraxner, F., 2015. "Biomethane as transport fuel – A comparison with other biogas utilization pathways in northern Italy," Applied Energy, Elsevier, vol. 157(C), pages 25-34.
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