Applied Machine Learning for Solar Data Processing

 

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  • Product Description
 

It is becoming increasingly important to understand the possible cause and effect relationships between these solar events and features to produce timely and reliable computer-based forecasting of extreme solar events. These forecasts are very important for protecting our technological infra-structures and human life on earth and in space. The need to develop automated tools to process solar data is also increasing because existing space missions are sending huge amounts of data and scientists back on Earth are struggling to keep pace. In this book, we present our research work introducing novel, fully computerised, machine learning-based decision rules and models that can be used within a system design for automated space weather forecasting. The system design in this book consists of three stages: (1) designing computer tools to find the associations among solar events and features (2) applying machine learning algorithms to the associations? datasets and (3) studying the evolution patterns of sunspot groups using time-series methods.

Product Specifications
SKU :COC101210
AuthorMohammad H. Alomari,Rami S. Qahwaji and Stanley S. Ipson
LanguageEnglish
BindingPaperback
Number of Pages152
Publishing Year2011-09-22T00:00:00.000
ISBN978-3845477763
Edition1 st
Book TypePhysics
Country of ManufactureIndia
Product BrandLAP LAMBERT Academic Publishing
Product Packaging InfoBox
In The Box1 Piece
Product First Available On ClickOnCare.com2015-08-18 00:00:00
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