Development of a Data Mining Application for Agriculture Based on Bayesian Networks

Abstract

Abstract:Data mining is a process by which the data can be analyzed so as to generate useful knowledge. It aims to use existing data to invent new facts and to uncover new relationships previously unknown even to experts. Bayesian network is a powerful tool for dealing with uncertainties, and has a widespread use in the area of data mining. In this paper, we focus on development of a data mining application for agriculture based on Bayesian networks. Let features (or objects) as variables or the nodes in Bayesian network, let directed edges present the relationships between features, and the relevancy intensity can be regarded as confidence between the variables. Accordingly, it can find the relationships in the agricultural data by learning a Bayesian network. After defining the domain variables and data preparation, we construct a model for agricultural application based on Bayesian network learning method. The experimental results indicate that the proposed method is feasible and efficient, and it is a promising approach for data mining in agricultural data.

Mining the Impact of Climate Change on Animal Production

“…Data mining is the process of using computer algorithms to seek valuable generalizations from databases of stored information, or from continually occurring information. The aim of the data mining is to analysis existing data to discover new facts and new relationships previously unknown even to experts [5]. Data mining, as defined by [8], "is the process of non-trivial extraction of implicit, previously unknown and potentially useful information from data in large databases".…”

“…Data mining provides an information technology which utilizes the data. It is very helpful for decision making since it extract regulations, patterns and models from large databases [5]. It analysis the large quantities data sets to discover relationships and to summarize the data in new ways that are understandable and useful to the data user [6].…”

Using Data Mining to Predict the Concentration of Cadmium in Khuzestan Paddies, Iran

“…In a broad sense, any method that extracts information from data can be regarded as data mining, which includes a variety of information processing methods (5). Data mining is widely developed in various applications such as agriculture (6), analysis of organic matter (7), medical diagnosis (8), product design (9), marketing (10), credit card fraud detection (11), financial forecasting (12), and automatic abstraction (13).…”