International Journal of Advances in Computer Science and Its Applications
Author(s) : B VISHNU VARDHAN , D RAMESH
Indian Gross Domestic Product (GDP) is largely depends on agricultural production. Agricultural production is the product of cultivated area and average yield per unit area. Its impact on the welfare of the country is much greater and nearly 70% of the working population depends on agricultural activities for their livelihood. Agrarian sector in India is facing a severe problem to maximize crop productivity. More than 60 % of the crop in India still depends solely on monsoon rainfall (Central Statistical Organization, 2008). An analysis of past climatic variations and its impact on agricultural production is presented in this paper to get the climate variability on agriculture. Recent development in Information Technology enabled new methods to adopt in agriculture sector. High end servers and the latest software in analytics are useful for predicting certain crop production. Clustering approach is used for estimating the future year’s rice production based on average rain fall of specific region. Multiple Linear Regression is a statistical data mining technique which is adopted in this paper for predicting rice yield expectation in the regions of Andhra Pradesh, India.