An Integrated Prediction and Optimization Model of a Thermal Energy Production System in a Factory Producing Furniture Components
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- Mostafa A. Rushdi & Ahmad A. Rushdi & Tarek N. Dief & Amr M. Halawa & Shigeo Yoshida & Roland Schmehl, 2020. "Power Prediction of Airborne Wind Energy Systems Using Multivariate Machine Learning," Energies, MDPI, vol. 13(9), pages 1-23, May.
- Wang, Chunlin & Liu, Yang & Zheng, Song & Jiang, Aipeng, 2018. "Optimizing combustion of coal fired boilers for reducing NOx emission using Gaussian Process," Energy, Elsevier, vol. 153(C), pages 149-158.
- Cai, Yongtie & Tay, Kunlin & Zheng, Zhimin & Yang, Wenming & Wang, Hui & Zeng, Guang & Li, Zhiwang & Keng Boon, Siah & Subbaiah, Prabakaran, 2018. "Modeling of ash formation and deposition processes in coal and biomass fired boilers: A comprehensive review," Applied Energy, Elsevier, vol. 230(C), pages 1447-1544.
- Andrew Kusiak & Xiupeng Wei, 2014. "Prediction of methane production in wastewater treatment facility: a data-mining approach," Annals of Operations Research, Springer, vol. 216(1), pages 71-81, May.
- Böhler, Lukas & Görtler, Gregor & Krail, Jürgen & Kozek, Martin, 2019. "Carbon monoxide emission models for small-scale biomass combustion of wooden pellets," Applied Energy, Elsevier, vol. 254(C).
- Liukkonen, M. & Heikkinen, M. & Hiltunen, T. & Hälikkä, E. & Kuivalainen, R. & Hiltunen, Y., 2011. "Artificial neural networks for analysis of process states in fluidized bed combustion," Energy, Elsevier, vol. 36(1), pages 339-347.
- Lv, You & Liu, Jizhen & Yang, Tingting & Zeng, Deliang, 2013. "A novel least squares support vector machine ensemble model for NOx emission prediction of a coal-fired boiler," Energy, Elsevier, vol. 55(C), pages 319-329.
- Tianfei Sun & Bizhong Xia & Yifan Liu & Yongzhi Lai & Weiwei Zheng & Huawen Wang & Wei Wang & Mingwang Wang, 2019. "A Novel Hybrid Prognostic Approach for Remaining Useful Life Estimation of Lithium-Ion Batteries," Energies, MDPI, vol. 12(19), pages 1-22, September.
- Costa, M. & Massarotti, N. & Indrizzi, V. & Rajh, B. & Yin, C. & Samec, N., 2014. "Engineering bed models for solid fuel conversion process in grate-fired boilers," Energy, Elsevier, vol. 77(C), pages 244-253.
- Shi, Yan & Zhong, Wenqi & Chen, Xi & Yu, A.B. & Li, Jie, 2019. "Combustion optimization of ultra supercritical boiler based on artificial intelligence," Energy, Elsevier, vol. 170(C), pages 804-817.
- Tóth, Pál & Garami, Attila & Csordás, Bernadett, 2017. "Image-based deep neural network prediction of the heat output of a step-grate biomass boiler," Applied Energy, Elsevier, vol. 200(C), pages 155-169.
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- Paweł Tomtas & Amadeusz Skwiot & Elżbieta Sobiecka & Andrzej Obraniak & Katarzyna Ławińska & Tomasz P. Olejnik, 2021. "Bench Tests and CFD Simulations of Liquid–Gas Phase Separation Modeling with Simultaneous Liquid Transport and Mechanical Foam Destruction," Energies, MDPI, vol. 14(6), pages 1-14, March.
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Keywords
machine learning; artificial neural network; particle swarm optimization; importance analysis; thermal energy; grate-fired boiler;All these keywords.
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