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Efficient Dissemination of Rainfall Forecasting to Safeguard Farmers from Crop Failure Using Optimized Neural Network Model


Balamurali Ananthanarayanan1*,Siva Balan2,Anu Meera Balamurali3,Karthika Balamurali4


1Fishing Harbour Project Division, Fisheries Dept, Govt of Tamilnadu, India
2Noorul Islam University, Tamilnadu, India
3Anna university, Guindy campus, Chennai, India
4Tata consultancy Services, Bangalore, Karnataka, India


In the field of weather forecasting, especially in rainfall prediction many researchers employed different data mining techniques. There is numerous method of organizing agricultural engineering substance and it remains an open research issue particularly when taking to distinctive arrangements of clients - farmers, agricultural engineers, agri-organizations -both from proficiency point of view. Keeping these factors Indian farmers in mind, we have chosen to do research on efficient dissemination of rainfall forecasting to safeguard farmers from crop failure using optimized neural network (NN) model. Here, at first, we generate the feature matrix based on five feature indicator. Once the feature matrix is formed, the prediction is done based on the hybrid classifier. In hybrid classifier, particle swarm optimization algorithm is combined with Grey Wolf optimization for training the RBF NN. The performance of the algorithm is analyzed with the help of real datasets gathered from pechiparai and perunchani regions.


Rainfall prediction, Hybrid classifier, Feature indicator, PSO, GWO, RBF, Neural network.

Full Text:

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