Application of permutation genetic algorithm for sequential model building–model validation design of experiments
- Submitting institution
-
The University of Bradford
- Unit of assessment
- 12 - Engineering
- Output identifier
- 69
- Type
- D - Journal article
- DOI
-
10.1007/s00500-015-1929-5
- Title of journal
- Soft Computing
- Article number
- -
- First page
- 3023
- Volume
- 20
- Issue
- 8
- ISSN
- 1432-7643
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2015
- URL
-
https://link.springer.com/article/10.1007%2Fs00500-015-1929-5
- 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
-
2
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Significant output from the £9m CREO TSB project (Ford, JLR + 9 other partners, 2011-13) delivering a more efficient approach to expensive mapping and calibration engine experiments. Led to further funding from JLR Powertrain Research to develop a MATLAB toolbox to implement the method for JLR use. Methodology and toolbox subsequently used in the Multi-Physics Engine Modelling research project funded by JLR (2015-19) and embedded in CPD Short Course material for the JLR/TAS framework (over 200 engineers trained). Dr Kianifar (PhD researcher) went on to work for Perkins Caterpillar as senior virtual calibration engineer.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
