DOI: 10.5176/2251-189X_SEES17.9

Authors: Anand V, Narendran R and Paramasivam A

Abstract: Rice being the staple food in India occupies an important role in the country’s agrarian economy. India also stands second in human population in the world. So it is of at most importance to study the relationship between the rice production and human population. In this work, a Lotka- Volterra model is proposed for analyzing Indian population and India’s rice production from 1951 to 2013. The parameters of the model are estimated using genetic algorithm. The Maximum Entropy Principle (MEP) is used to get the best estimates of the sampled data by maximising the entropy of the model. The entropy for the actual and developed model is calculated using Shannon’s entropy. Further, the international standards of performance indices are computed along with the mean square error to evaluate the overall performance of the model. Results demonstrate that by maximizing the entropy of the Lotka-Volterra model, better estimates of the sample data are obtained and the error is found to be minimal. The performance too has been validated by the values of performance indices.

Keywords: Lotka-Volterra model, Maximum Entropy Principle (MEP), Human Population, Rice Production

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