Details of Grant 

EPSRC Reference:	GR/T17588/01
Title:	Image Processing and Machine Learning Techniques for Short-Term Prediction of Solar Activity
Principal Investigator:	Qahwaji, Professor R
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department:	Electronic Imaging & Media Communication
Organisation:	University of Bradford
Scheme:	First Grant Scheme Pre-FEC
Starts:	10 January 2005	Ends:	09 January 2008	Value (£):	124,887
EPSRC Research Topic Classifications:	Image & Vision Computing
EPSRC Industrial Sector Classifications:	Information Technologies
Related Grants:
Panel History:
Summary on Grant Application Form
This project aims to create a computer application environment for handling a real-life problem, which is the prediction of solar events (flares and coronal mass ejections (CMEs)) that have severe effects on Earth. Solar activity can cause severe problems for the space industry; earth based electromagnetic communications and power systems, radio transmission and so on. A machine learning environment will be developed to provide shortterm prediction for the occurrence of these events, based on the data available in public catalogues for other solar features. The timing of this project coincides with the near release of the EGSO (European Grid of Solar Observatories) project catalogues. For the first time, the scattered representations for the solar data from ground and space observatories from all over the world will be unified into a few catalogues that will be made available publicly on the web. The wealth of data provided by these catalogues will not be fully exploited without efficient knowledge extraction and machine learning algorithms that will enable us to understand the correlation between different solar features and solar events. In this project, a range of image processing and pattern classification algorithms will be implemented to extract features and provide efficient low-level representation that will enable knowledge extraction using machine learning algorithms. This project will deliver a platform for solar-feature monitoring and short-term solar event prediction.
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Organisation Website:	http://www.brad.ac.uk