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Paper Title : ARMA BASED CROP YIELD PREDICTION USING TEMPERATURE AND RAINFALL PARAMETERS WITH GROUND WATER LEVEL CLASSIFICATION

ISSN : 2395-1303
Year of Publication : 2020
10.29126/23951303/IJET-V6I2P6

Authors: -Mr.S.Jagadeesan, M.E.,Mr. T.Gopinath, MCA

         


Abstract
The main aim of this project is to provide a methodology for crop yield production based on the historical climatic and production data. Crop yield prediction based on the previous years of temperature and rainfall can help farmers take necessary steps to improve crop yield in the coming season. Understanding crop yield can help ensure food security and reduce impacts of climate change. Crops are sensitive to various weather phenomena such as temperature and rainfall. Therefore, it becomes crucial to include these features when predicting the yield of a crop. Weather the forecasting are complicated process. In this work, ARMA (Auto Regressive Moving Average) method is used to forecast crop yield. Past ten years of data set is taken for temperature, rainfall and ground water level for our country. Yield prediction is then carried out using a Fuzzy logic algorithm to better judge the crop yield. In addition, this project classifies the ground water level data set records using KNN to predict the model for future test record data sets. It will be helpful in analyzing the ground water levels in the past and so as to predict the future levels.

Reference
[1] P. Kumar "Crop yield forecasting by adaptive neuro fuzzy inference system." Mathematical Theory and Modeling 1.3, pp. 1-7, 2011. [2] I. Kaushik, and S.M. Singh. "Seasonal ARIMA model for forecasting of monthly rainfall and temperature." Journal of Environmental Research and Development 3, no. 2, pp. 506- 514, 2008. [3] S. Veenadhari, B. Misra, and C. D. Singh. "Machine learning approach for forecasting crop yield based on climatic parameters." 2014 International Conference on Computer Communication and Informatics, pp. 1-5. IEEE, 2014. [4] S. Prabakaran, P.N. Kumar, and P.S.M. Tarun. "Rainfall prediction using modified linear regression”, 2006. [5] S.K. Mohapatra, A. Upadhyay, and C. Gola. "Rainfall prediction based on 100 years of meteorological data." 2017 International Conference on Computing and Communication Technologies for Smart Nation (IC3TSN), pp. 162-166. IEEE, 2017. [6] L. A. Zadeh, “Fuzzy sets,” Information and Control, pp. 338-353, 1965.

Keywords
ARMA, yield predicition, KNN Algorithm..