Improving energy efficiency prediction under aberrant measurement using deep compensation networks: A case study of petrochemical process
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DOI: 10.1016/j.energy.2022.125837
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- Bardeeniz, Santi & Panjapornpon, Chanin & Fongsamut, Chalermpan & Ngaotrakanwiwat, Pailin & Hussain, Mohamed Azlan, 2024. "Energy efficiency characteristics analysis for process diagnosis under anomaly using self-adaptive-based SHAP guided optimization," Energy, Elsevier, vol. 309(C).
- Gong, Shixin, 2023. "Multi-scale energy efficiency recognition and diagnosis scheme for ethylene production based on a hierarchical multi-indicator system," Energy, Elsevier, vol. 267(C).
- Ma, Jinjin & Yang, Lin & Wang, Donghan & Li, Yiming & Xie, Zuomiao & Lv, Haodong & Woo, Donghyup, 2024. "Digitalization in response to carbon neutrality: Mechanisms, effects and prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
- Lv, Mingyang & Gou, Kaijie & Chen, Heng & Lei, Jing & Zhang, Guoqiang & Liu, Tao, 2024. "Optimal Design of Wind-Solar complementary power generation systems considering the maximum capacity of renewable energy," Energy, Elsevier, vol. 312(C).
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Keywords
Energy efficiency prediction; Deep compensation network; Petrochemical process; Measurement reliability;All these keywords.
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