An Analysis of Data Mining Techniques to Analyze the Effect of Weather on Agriculture

With the growing needs of Agriculture sector, the farmers and stakeholders need to make important decisions influenced by various factors like soil type, pollution level, humidity, temperature, rainfall, geographic attributes etc. This paper deliberates about the various data mining techniques that analyze the environmental factors that affect the agricultural parameters. These techniques give solution to various decision making problems faced by the agriculture sector today. In this paper we focus on optimizing effect of weather on agriculture using various techniques like Correlation Analysis, multidimensional modeling, k-means, ANN, SVM, KG classification, PAM, CLARA, DBSCAN etc. This information can help our farmers to increase their production based on the behavior of the climate of their location.