优化锅炉低氮转换策略及智能相变控制和热管理:从复合神经网络预测和光学图像分析的角度看问题

IF 1.7 4区 工程技术 Q4 ENERGY & FUELS
Rui Sun, Yihuan Huang, Chao Sun
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引用次数: 0

摘要

从复合神经网络预测和优化的角度研究了锅炉低氮转化技术、智能相变控制和热管理的优化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization of Boiler Low Nitrogen Conversion Strategy and Intelligent Phase Change Control and Thermal Management: From the Perspective of Compound Neural Network Prediction and Optical Image Analysis
The optimization of boiler low nitrogen conversion technology, intelligent phase change control and thermal management are studied from the perspective of compound neural network prediction and opt...
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来源期刊
Combustion Science and Technology
Combustion Science and Technology 工程技术-工程:化工
CiteScore
4.10
自引率
10.50%
发文量
182
审稿时长
8.3 months
期刊介绍: Combustion Science and Technology is an international journal which provides for open discussion and prompt publication of new results, discoveries and developments in the various disciplines which constitute the field of combustion. The editors invite original contributions dealing with flame and fire research, flame radiation, chemical fuels and propellants, reacting flows, thermochemistry, material synthesis, atmospheric chemistry and combustion phenomena related to aircraft gas turbines, chemical rockets, ramjets, automotive engines, furnaces and environmental studies. In so doing, the editors hope to establish a central vehicle for the rapid exchange of ideas and results emanating from the many diverse areas associated with combustion. Accordingly, both full-length papers on comprehensive studies, and communications of significant, but not fully explored, theoretical or experimental developments are included in the journal together with unsolicited and solicited comments on published matter and yearly, cumulative indices.
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