Comparative Study Among Lease Square Method, Steepest Descent Method, and Conjugate Gradient Method for Atmopsheric Sounder Data Analysis
Journal Title: International Journal of Advanced Research in Artificial Intelligence(IJARAI) - Year 2013, Vol 2, Issue 9
Abstract
Comparative study among Least Square Method: LSM, Steepest Descent Method: SDM, and Conjugate Gradient Method: CGM for atmospheric sounder data analysis (estimation of vertical profiles for water vapor) is conducted. Through simulation studies, it is found that CGM shows the best estimation accuracy followed by SDM and LSM. Method dependency on atmospheric models is also clarified.
Authors and Affiliations
Kohei Arai
Keywords
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