Operation optimization of Shell coal gasification process based on convolutional neural network models
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Operation optimization of Shell coal gasification process based on convolutional neural network models
Authors
Keywords
Convolutional neural network, Operation optimization, Shell coal gasification process, Prior physical knowledge, Simplified mechanistic model
Journal
APPLIED ENERGY
Volume 292, Issue -, Pages 116847
Publisher
Elsevier BV
Online
2021-04-08
DOI
10.1016/j.apenergy.2021.116847
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- The mutual benefits of renewables and carbon capture: Achieved by an artificial intelligent scheduling strategy
- (2021) Xianhao Chen et al. ENERGY CONVERSION AND MANAGEMENT
- Intelligent predictive control of large-scale solvent-based CO2 capture plant using artificial neural network and particle swarm optimization
- (2020) Xiao Wu et al. ENERGY
- Dynamic modeling, systematic analysis, and operation optimization for shell entrained-flow heavy residue gasifier
- (2020) Zhikai Cao et al. ENERGY
- Simultaneous parametric optimization for design and operation of solvent-based post-combustion carbon capture using particle swarm optimization
- (2020) Han Xi et al. APPLIED THERMAL ENGINEERING
- Dynamic soft sensor development based on convolutional neural networks
- (2019) Kangcheng Wang et al. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
- Modelling and optimization of a pilot-scale entrained-flow gasifier using artificial neural networks
- (2019) Han Wang et al. ENERGY
- Broad Convolutional Neural Network Based Industrial Process Fault Diagnosis With Incremental Learning Capability
- (2019) Wanke Yu et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- Deep convolutional neural network model based chemical process fault diagnosis
- (2018) Hao Wu et al. COMPUTERS & CHEMICAL ENGINEERING
- On-line simulation and optimization of a commercial-scale shell entrained-flow gasifier using a novel dynamic reduced order model
- (2018) Hua Zhou et al. ENERGY
- Deep Learning-Based Feature Representation and Its Application for Soft Sensor Modeling With Variable-Wise Weighted SAE
- (2018) Xiaofeng Yuan et al. IEEE Transactions on Industrial Informatics
- Evaluation of the energy efficiency of the shell coal gasification process by coal type
- (2017) Youngsan Ju et al. ENERGY CONVERSION AND MANAGEMENT
- Multi-objective operation optimization of a Distributed Energy System for a large-scale utility customer
- (2016) Marialaura Di Somma et al. APPLIED THERMAL ENGINEERING
- Fruit fly optimization algorithm based on differential evolution and its application on gasification process operation optimization
- (2015) Jinwei Niu et al. KNOWLEDGE-BASED SYSTEMS
- Dynamic modeling of Shell entrained flow gasifier in an integrated gasification combined cycle process
- (2014) Hyeon-Hui Lee et al. APPLIED ENERGY
- Compartment modeling of coal gasification in an entrained flow gasifier: A study on the influence of operating conditions
- (2014) Xiangdong Kong et al. ENERGY CONVERSION AND MANAGEMENT
- Convolutional Neural Networks for Speech Recognition
- (2014) Ossama Abdel-Hamid et al. IEEE-ACM Transactions on Audio Speech and Language Processing
- Flow and heat transfer characteristics in the syngas quench system of a 300 MWe IGCC process
- (2013) In-Soo Ye et al. APPLIED THERMAL ENGINEERING
- Taguchi approach for co-gasification optimization of torrefied biomass and coal
- (2013) Wei-Hsin Chen et al. BIORESOURCE TECHNOLOGY
- Numerical investigation on performance of coal gasification under various injection patterns in an entrained flow gasifier
- (2012) Chih-Jung Chen et al. APPLIED ENERGY
- Reduced order modeling of the Shell–Prenflo entrained flow gasifier
- (2012) Matteo Gazzani et al. FUEL
- Integrated gasification combined cycle (IGCC) process simulation and optimization
- (2009) F. Emun et al. COMPUTERS & CHEMICAL ENGINEERING
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started