Dynamic optimization of industrial processes with nonuniform discretization-based control vector parameterization
- Submitting institution
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Glasgow Caledonian University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 33290100
- Type
- D - Journal article
- DOI
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10.1109/TASE.2013.2292582
- Title of journal
- IEEE Transactions on Automation Science and Engineering
- Article number
- -
- First page
- 1289
- Volume
- 11
- Issue
- 4
- ISSN
- 1545-5955
- Open access status
- Out of scope for open access requirements
- Month of publication
- October
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
5
- Research group(s)
-
-
- Citation count
- 21
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper is from the long-term collaboration with East China University of Science and Technology, Shanghai, China. The work was funded by Chinese government, including the National Basic Research Programme, the National Natural Science Foundation, the Outstanding Researcher Programme of the Ministry of Education, and the Shanghai City Government. The paper has laid a benchmark foundation for follow-up journal publications in swarm intelligence optimisation, including Applied Soft Computing (volume 45, 2016, Elsevier), Soft Computing (volume 21, 2017, Springer), Swarm and Evolutionary Computation (Volume 45, 2019, Elsevier), and Multiagent and Grid Systems (volume 16, 2020, IOS Press).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -