• SURJEET KUMAR
• MANAS KUMAR SANYAL
• SATYENDRA NATH MANDAL

There are many statistical based predictive models for prediction of productivity of rice. In this paper, a hybrid model using statistic and neural network is used to predict the production of rice in India. The statistics equations like linear, Exponential, Fourier, Gaussian, Polynomial are applied on time series data. One equation is selected based on minimum average error. The values of constants of selected equation are further modified using neural network. It is observed that the error of prediction is further minimized using statistic neuron mode compare to prediction based on statistic.

Time Series Data, Soft Computing Model, Statistical Models, Neural Network, Average Error

"Prediction of Rice Production of India Using Neuro Static Model", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.601-610, December-2018, Available :http://www.jetir.org/papers/JETIR1812778.pdf

"Prediction of Rice Production of India Using Neuro Static Model", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp601-610, December-2018, Available at : http://www.jetir.org/papers/JETIR1812778.pdf