Data-driven multi-objective optimisation of coal-fired boiler combustion systems-Reference-Cited by-同舟云学术

Data-driven multi-objective optimisation of coal-fired boiler combustion systems

Published:2018-11 Issue: Volume:229 Page:446-458
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Rahat Alma A.M.,Wang Chunlin,Everson Richard M.,Fieldsend Jonathan E.

Funder

Engineering and Physical Sciences Research Council, United Kingdom

National Natural Science Foundation of China

China Scholarship Council

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference40 articles.

1. When will fossil fuel reserves be diminished?;Shafiee;Energy Policy,2009

2. Moretti AL, Jones CS, Asia P-G. Advanced emissions control technologies for coal-fired power plants. Babcock & Wilcox Power Generation Group; BR-1886.

3. Primary air pollutant emissions of coal-fired power plants in china: Current status and future prediction;Zhao;Atmos Environ,2008

4. Control of combustion-generated nitrogen oxide emissions: Technology driven by regulation;Bowman;Symp (Int) Combust,1992

5. Multi-step-ahead prediction of NOx emissions for a coal-based boiler;Smrekar;Appl Energy,2013

Cited by 55 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A predictive model with time-varying delays employing channel equalization convolutional neural network for NOx emissions in flexible power generation;Energy;2024-10

2. A novel data-driven approach for coal-fired boiler under deep peak shaving to predict and optimize NOx emission and heat exchange performance;Energy;2024-09

3. Steam generator efficiency optimization under uncertainty through multi-fidelity modeling;Journal of Computational Science;2024-07

4. Combustion process modeling based on deep sparse least squares support vector regression;Engineering Applications of Artificial Intelligence;2024-06

5. Multi-condition operational optimization with adaptive knowledge transfer for municipal solid waste incineration process;Expert Systems with Applications;2024-03