A Survey on Crop Yield Prediction using Data Mining
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2018 by IJCTT Journal|
|Year of Publication : 2018|
|Authors : Mythra.N, Dr.Velayudham.A, Dr.Shamila.E.S, Pavithra.M|
|DOI : 10.14445/22312803/IJCTT-V65P101|
MLA Style: Mythra.N, Dr.Velayudham.A, Dr.Shamila.E.S, Pavithra.M "A Survey on Crop Yield Prediction using Data Mining" International Journal of Computer Trends and Technology 65.1 (2018): 1-7.
APA Style:Mythra.N, Dr.Velayudham.A, Dr.Shamila.E.S, Pavithra.M (2018). A Survey on Crop Yield Prediction using Data Mining. International Journal of Computer Trends and Technology, 65(1), 1-7.
Now-a –days the most important emerging field in the real world is agriculture and it is the main occupation and backbone of our country. The most of the primary and secondary business is based on farming and it plays the main role in our Indian economy. In farming, season cultivation of the crop is based on the soil. Another important work in agriculture is selecting soil is based on the weather condition and also when to harvest the crop for the best cultivation. Data mining techniques is very popular in the Area of agriculture. Data mining is the process of finding the new templates from the large data sets there are various data mining techniques are used and evaluated in agriculture for estimating the future year’s crop production. Utilization of information and communications technology enables automation of extracting significant data in an effort to obtain knowledge and trends crop is an essential key factor of agriculture. So data mining techniques are useful for new framers. This paper presents a brief comparative study of various papers that deals with various techniques used to figure out the crop yield different data mining techniques that are in the use for crop yield estimation in agriculture. Recently data processing techniques in agriculture required decide, storage, monitored and retrieval the resource used this survey aims to search out appropriate data processing models to realize high accuracy and prediction capabilities.
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Data Mining, Agriculture, framer, Crop Selection, soil selection, methodology, high accuracy, prediction capabilities.