| EPSRC Reference: |
EP/F057997/1 |
| Title: |
Gene Expression Programming - a new machine learning technique for supervised and unsupervised classification |
| Principal Investigator: |
Teodorescu, Dr L |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Sch of Engineering and Design |
| Organisation: |
Brunel University London |
| Scheme: |
First Grant Scheme |
| Starts: |
01 October 2008 |
Ends: |
31 March 2012 |
Value (£): |
249,001
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| EPSRC Research Topic Classifications: |
| Artificial Intelligence |
New & Emerging Comp. Paradigms |
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| EPSRC Industrial Sector Classifications: |
| No relevance to Underpinning Sectors |
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| Related Grants: |
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| Panel History: |
| Panel Date | Panel Name | Outcome |
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03 Mar 2008
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ICT Prioritisation Panel (Technology)
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Announced
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Summary on Grant Application Form |
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Many scientific, engineering and business fields such as genetics, medicine, environment science and engineering, physics, astronomy, finance, and marketing are facing common challenges in dealing with complex data for extracting field-specific knowledge. Efficient data analysis techniques are needed in order to intelligently assist the user in extracting this knowledge. This project will address this need using the basic ideas of a recently developed computer algorithm, Gene Expression Programming, for the development of novel evolutionary algorithms techniques and novel supervised and unsupervised data classification algorithms. The project will develop and exploit novel homologous genetic operators, and mechanisms to control the redundant information in the solutions provided by the algorithm in order to increase its efficiency. These developments will be combined with state-of-the-art statistical methods such as boosting learning in order to create efficient data classification algorithms.The methods and algorithms developed in the project will be implemented in software applications made available as open-source in order to maximize the spectrum of the beneficiaries of the project outcomes.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.brunel.ac.uk |