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contributor authorZuo, Qiang
contributor authorHe, Jiale
contributor authorAL-Bukhaiti, Khalil
contributor authorWan, Anping
contributor authorCheng, Xiaomin
contributor authorJi, Xiaosheng
date accessioned2026-08-20T11:57:01Z
date available2026-08-20T11:57:01Z
date copyright2026/03/20
date issued2026
identifier otherJOEEDU.EEENG-8542.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4312885
description abstractAbstractThis study presents TEBA-Net, an advanced deep learning model for simultaneous prediction of NOx and SO2 emissions from coal-fired combined heat and power (CHP) plants. The model integrates temporal convolutional networks (TCN), bidirectional ...Practical ApplicationsThe TEBA-Net model and its associated dynamic chemical treatment strategy offer significant industrial relevance by enabling real-time optimization of limestone slurry and ammonia injection rates in combined heat and power (CHP) ...
publisherAmerican Society of Civil Engineers
titlePredicting NOx and SO2 Emissions in CHP Systems with TEBA-Net for Sustainable Operations
typeJournal Article
journal volume152
journal issue6
journal titleJournal of Environmental Engineering
identifier doi10.1061/JOEEDU.EEENG-8542
journal fristpage04026018-1
journal lastpage04026018-13
page13
treeJournal of Environmental Engineering:;2026:;Volume ( 152 ):;issue: 006
contenttypeFulltext


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