Faithin Omaha eBook Collection

Download or read book Enhanced Flare Prediction by Advanced Feature Extraction from Solar Images written by Omar Wahab Ahmed and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Space weather has become an international issue due to the catastrophic impactit can have on modern societies. Solar flares are one of the major solar activities thatdrive space weather and yet their occurrence is not fully understood. Research isrequired to yield a better understanding of flare occurrence and enable the developmentof an accurate flare prediction system, which can warn industries most at risk to takepreventative measures to mitigate or avoid the effects of space weather. This thesisintroduces novel technologies developed by combining advances in statistical physics, image processing, machine learning, and feature selection algorithms, with advances insolar physics in order to extract valuable knowledge from historical solar data, related toactive regions and flares. The aim of this thesis is to achieve the followings: i) Thedesign of a new measurement, inspired by the physical Ising model, to estimate themagnetic complexity in active regions using solar images and an investigation of thismeasurement in relation to flare occurrence. The proposed name of the measurement isthe Ising Magnetic Complexity (IMC). ii) Determination of the flare predictioncapability of active region properties generated by the new active region detectionsystem SMART (Solar Monitor Active Region Tracking) to enable the design of a newflare prediction system. iii) Determination of the active region properties that are mostrelated to flare occurrence in order to enhance understanding of the underlying physicsbehind flare occurrence. The achieved results can be summarised as follows: i) The newactive region measurement (IMC) appears to be related to flare occurrence and it has apotential use in predicting flare occurrence and location. ii) Combining machinelearning with SMART's active region properties has the potential to provide moreaccurate flare predictions than the current flare prediction systems i.e. ASAP(Automated Solar Activity Prediction). iii) Reduced set of 6 active region propertiesseems to be the most significant properties related to flare occurrence and they canachieve similar degree of flare prediction accuracy as the full 21 SMART active regionproperties. The developed technologies and the findings achieved in this thesis willwork as a corner stone to enhance the accuracy of flare prediction; develop efficientflare prediction systems; and enhance our understanding of flare occurrence. Thealgorithms, implementation, results, and future work are explained in this thesis.