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Investigate UCI’s “Solar Flare Dataset” to have basic understanding of their significance and meaning: Computer Science Case Study, NU, UK

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Investigate UCI’s “Solar Flare Dataset” to have basic understanding of their significance and meaning: Computer Science Case Study, NU, UK

UniversityNorthumbria University (NU)
SubjectComputer Science Case Study

tasks:

Investigate UCI’s “Solar Flare Dataset” to have basic understanding of their significance and meaning. 

Develop basic data processing tools to read samples of data
Extract the relevant data records that will support the development of your ideas
Propose and develop an AI system that can be implemented to demonstrate your ideas 
Demonstrate the feasibility of your design by implementing some of its basic features using python
Discuss your findings making recommendations for further investigation and improved implementation.
Write a 1500 words report to present your work and findings.

Useful Reading
T Colak, R Qahwaji, "Automated solar activity prediction: a hybrid computer platform using machine learning and solar imaging for automated prediction of solar flares," Space Weather 7(6),128,2009
OW Ahmed, R Qahwaji, T Colak, PA Higgins, PT Gallagher, et al, "Solar flare prediction using advanced feature extraction, machine learning, and feature selection," Solar Physics 283 (1), 157-175, 2013

Effort required
The coursework is worth 50% of the module marks. You are expected to demonstrate good effort in exploring the background of this problem, understanding the datasets, processing the data, developing meaningful AI system and implementing some basic aspects, and writing up your report. The coursework is worth 50% of the marks for this 20-credit module. A 20-credit module is nominally 200 hours of your time, some of which is spent in lectures, labs and private study. You should expect to be spending around 70 hours on this coursework.

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