Prediction Of Rainfall In India To Increase Agricultural Productivity Implemented In Hadoop

  • D. Anantha Reddy, Dr. Rakesh Tripathi, Dr. Sanjay Kumar

Abstract

Indian agriculture mainly depend on the rainfall rate, major amount of cultivation is done based on the rain. If the rain fall rate is low then automatically the productivity in agriculture is also low. We are going to predict the future rain fall rate based on the past years. If we predict the future rain fall rate then automatically it will reflect on agriculture then it increases the income in agriculture. Agriculture productivity in India play important role in economy of country.  Indian agriculture is mainly based on the old traditional way of cultivation. We can replace the traditional way of cultivation with new way of using past data and statistics. To help the farmers in India our prediction and analysis. To predict the rain fall rate, Data Mining technique, clustering (modified k-Means) used. But now days the data size is increased dramatically and data is available in variety forms such as structured and un-structured for such reason we have gone through Hadoop Single Node Cluster to estimate the rainfall rate. To better understand, the results are presented in Orange tool.

Published
2020-06-04
How to Cite
D. Anantha Reddy, Dr. Rakesh Tripathi, Dr. Sanjay Kumar. (2020). Prediction Of Rainfall In India To Increase Agricultural Productivity Implemented In Hadoop. International Journal of Advanced Science and Technology, 29(9s), 7433-7442. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/24496