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Data Mining in Agriculture on Crop Price Prediction: Techniques and Applications

International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 99 - Number 12
Year of Publication: 2014
Manpreet Kaur
Heena Gulati
Harish Kundra

Manpreet Kaur, Heena Gulati and Harish Kundra. Article: Data Mining in Agriculture on Crop Price Prediction: Techniques and Applications. International Journal of Computer Applications 99(12):1-3, August 2014. Full text available. BibTeX

	author = {Manpreet Kaur and Heena Gulati and Harish Kundra},
	title = {Article: Data Mining in Agriculture on Crop Price Prediction: Techniques and Applications},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {99},
	number = {12},
	pages = {1-3},
	month = {August},
	note = {Full text available}


In agriculture crop price analysis, Data mining is emerging as an important research field. In this paper, we will discuss about the applications and techniques of Data mining in agriculture. There are various data mining techniques such as K-Means, K-Nearest Neighbor (KNN), Artificial Neural Networks (ANN) and Support Vector Machines (SVM) which are used for very recent applications of Data Mining techniques. This paper will consider the problem of price prediction of crops. Price Prediction, nowadays, has become very important agricultural problem which is to be solved only based on the available data. Data Mining techniques can be used to solve this problem. This work is based on finding suitable data models that helps in achieving high accuracy and generality for price prediction. For solving this problem, different Data Mining techniques were evaluated on different data sets.


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