A SURVEY OF SOIL TEMPERATURE AND MOISTURE PREDICTION TO RECOMMEND PLANTING DIFFERENT CROPS IN AGRICULTURE USING DATA MINING
Sri Vasavi College, Erode Self-Finance Wing, 3rd February 2017. National Conference on Computer and Communication, NCCC’17. International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)
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To obtain information or knowledge which can be helpful to farmers and government organizations for making better decisions and for make better policies which help to increased production. In this paper, our focus is on application of data mining techniques which is use to extract knowledge from the agricultural data to estimate better crop yield for major crops in major districts of India. It is very hard to acquire the information what really want with the accumulation of large number of data. In this paper our focus is on the applications of Data mining techniques in agricultural field. Generally for doing agriculture land, labor, capital and organization are required without that cannot produce with a new agriculture technology. Fuzzy sets are suitable for handling the issues related to understandability of pattern of incomplete data, and human interaction, mixed media information and can provide approximate solutions faster for given pattern of data. Yield prediction is a very important agricultural problem to farmer that remains to be solved based on the previous available data. The yield prediction problem can be solved by employing Data Mining techniques. This work aims to find suitable data models that achieve a high accuracy and a high generality in terms of yield prediction capabilities
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