Higher heating value prediction of high ash gasification-residues: Comparison of white, grey, and black box models
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DOI: 10.1016/j.energy.2023.129863
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- Büyükkanber, Kaan & Haykiri-Acma, Hanzade & Yaman, Serdar, 2023. "Calorific value prediction of coal and its optimization by machine learning based on limited samples in a wide range," Energy, Elsevier, vol. 277(C).
- Wilk, Małgorzata & Śliz, Maciej & Lubieniecki, Bogusław, 2021. "Hydrothermal co-carbonization of sewage sludge and fuel additives: Combustion performance of hydrochar," Renewable Energy, Elsevier, vol. 178(C), pages 1046-1056.
- Jahirul, M.I. & Rasul, M.G. & Brown, R.J. & Senadeera, W. & Hosen, M.A. & Haque, R. & Saha, S.C. & Mahlia, T.M.I., 2021. "Investigation of correlation between chemical composition and properties of biodiesel using principal component analysis (PCA) and artificial neural network (ANN)," Renewable Energy, Elsevier, vol. 168(C), pages 632-646.
- Qian, Wuyong & Wang, Jue, 2020. "An improved seasonal GM(1,1) model based on the HP filter for forecasting wind power generation in China," Energy, Elsevier, vol. 209(C).
- Dashti, Amir & Noushabadi, Abolfazl Sajadi & Asadi, Javad & Raji, Mojtaba & Chofreh, Abdoulmohammad Gholamzadeh & Klemeš, Jiří Jaromír & Mohammadi, Amir H., 2021. "Review of higher heating value of municipal solid waste based on analysis and smart modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
- Elmaz, Furkan & Yücel, Özgün & Mutlu, Ali Yener, 2020. "Predictive modeling of biomass gasification with machine learning-based regression methods," Energy, Elsevier, vol. 191(C).
- Changjun Huang & Lv Zhou & Fenliang Liu & Yuanzhi Cao & Zhong Liu & Yun Xue, 2023. "Deformation Prediction of Dam Based on Optimized Grey Verhulst Model," Mathematics, MDPI, vol. 11(7), pages 1-15, April.
- Wang, Dan & Tang, Yu-Ting & He, Jun & Yang, Fei & Robinson, Darren, 2021. "Generalized models to predict the lower heating value (LHV) of municipal solid waste (MSW)," Energy, Elsevier, vol. 216(C).
- Xing, Jiangkuan & Luo, Kun & Wang, Haiou & Gao, Zhengwei & Fan, Jianren, 2019. "A comprehensive study on estimating higher heating value of biomass from proximate and ultimate analysis with machine learning approaches," Energy, Elsevier, vol. 188(C).
- Vargas-Moreno, J.M. & Callejón-Ferre, A.J. & Pérez-Alonso, J. & Velázquez-Martí, B., 2012. "A review of the mathematical models for predicting the heating value of biomass materials," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3065-3083.
- Weiguo Dong & Zhiwen Chen & Jiacong Chen & Zhao Jia Ting & Rui Zhang & Guozhao Ji & Ming Zhao, 2022. "A Novel Method for the Estimation of Higher Heating Value of Municipal Solid Wastes," Energies, MDPI, vol. 15(7), pages 1-14, April.
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Keywords
Gasification residue; Higher heating value; Prediction models; Linear regression; Grey models; Artificial neural network;All these keywords.
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