A survey of data mining techniques applied to agriculture

被引：12

作者：

Mucherino A. ^{[1
]}

Papajorgji P. ^{[2
]}

Pardalos P.M. ^{[2
]}

机构：

[1] LIX, École Polytechnique, Palaiseau

[2] Center for Applied Optimization, University of Florida, Gainesville, FL

来源：

Operational Research | 2009年 / 9卷 / 2期

基金：

美国国家科学基金会;

关键词：

Agriculture; Artificial neural networks; Data mining; K nearest neighbor; K-means; Optimization; Support vector machines;

D O I：

10.1007/s12351-009-0054-6

中图分类号：

学科分类号：

摘要：

In this survey we present some of the most used data mining techniques in the field of agriculture. Some of these techniques, such as the k-means, the k nearest neighbor, artificial neural networks and support vector machines, are discussed and an application in agriculture for each of these techniques is presented. Data mining in agriculture is a relatively novel research field. It is our opinion that efficient techniques can be developed and tailored for solving complex agricultural problems using data mining. At the end of this survey we provide recommendations for future research directions in agriculture-related fields. © 2009 Springer-Verlag.

引用

页码：121 / 140

页数：19

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