I am working on assignment titled "Pattern Recognition of Rainfall using ANN". For training and validation proposes, i have time-series rainfall data ranging from 1976 – 2006 of two metro-logical stations.. I have arranged the data in EXCEL from where i import and convert it into matrices . Input matrix contains 480 * 5 . where 480 cloums with 5 rows representing
- Input= Year, Month, Longitude, Latitude and elevation
- Target= matrix contains mean rainfall(mm) value of that month with size of 480 * 1.
My questions are:
- What Kind of Neural Network will best to deal with this type of problem?
- Are the above parameters of Inputs and Targets are in correct format and valid for accurate and precise results?
I have used "nprtool" i.e; PattternNet and "lvqnet" Learning vector quantization neural network for this porpose. But my respected teacher suggests me to improve the results as overall regression value (0.25) of mentioned network was not satisfactory.
Thanks for your time….!
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