Weather based Crop Prediction by Deep Learning Model Source Code with Documentation

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Many advanced technologies are incorporated in the agricultural processes which enhances the crop yield production efficiency. The process of predicting the yield production regarding crop can be done by taking agriculturaldata that helps inanalyzing and making important decisions during the process of cultivation planning. This research work focuses on prediction of crop yield where two models were developed for this research work. Firstly:  a Genetic Algorithmis used, which reduces the input data size. Here some of the spatial information is used for the purpose of analysis,like: NDVI(Normalized Difference Vegetation Index),SPI(Standard Precipitation Index)and VCI(Vegetation Condition Index). Here there is reduction in the size of dataset, as during learning process the presence of similar data with multiple value increases the confusion and the resultant value gets deflected. 

In this research work a Modified Convolutional Neural Net (MCNN) with the use of Softmax function-an error correction technique is used,which leads to higher accuracy in the predicted results

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