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Research on Data Mining Technology Based on Ant Colony Algorithm

Author: TanHuaQin
Tutor: ZhongZuo
School: Wuhan University of Technology
Course: Applied Computer Technology
Keywords: Data Mining Cluster analysis Ant Colony Algorithm LF algorithm K-means algorithm
CLC: TP311.13
Type: Master's thesis
Year: 2006
Downloads: 455
Quote: 6
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Abstract


\strong vitality. Top Ten technical appraisal of the future of the domestic mainstream website, data mining technology accounted for a place, and today's world super company early into the research in the field of data mining, which includes IBM, Microsoft, and so on. Data mining is an interdisciplinary research areas related to database technology, artificial intelligence, machine learning, statistics, knowledge acquisition, biological computing theories and techniques of the discipline, its development will greatly impact the global information technology process. Comprehensive data mining technology, systematic, in-depth study is the objective needs of the development of information technology. In this paper, data mining technology, especially cluster analysis techniques were more in-depth research and analysis, put forward some ideas and improvements, mainly contains the following contents: Summary of data mining technology. Introduced the concept of data mining, a detailed classification of data mining technology. Summarizes the commonly used method of data mining, and data mining tasks summarized, and laid the foundation for the full swing of this article. The clustering analysis Technical Overview. The cluster analysis of data mining as an important component of valuable data distribution and data mode is mainly used in the potential of the data found. In this paper, the definition of cluster analysis, clustering methods, data types, and metrics of clustering results are briefly introduced. Overview of the ant colony algorithm. The ant colony algorithm is a new bionic algorithm derived from the nature of the living world. The algorithm is especially suitable for solving complex optimization problems, especially in discrete optimization problems. This article briefly describes the emergence and development of the ant colony algorithm, and elaborated the principle and implementation process of the algorithm. Clustering combination algorithm based on ant colony algorithm. Studied the basic ant colony clustering model based on information entropy and two classic cluster analysis algorithm: LF algorithm and K-means algorithm, first proposed a pheromone-based K-means improved algorithm, the algorithm criteria to cluster transition probabilities based on the pheromone to reduce the number of parameters of the algorithm to speed up the process of clustering. And in-depth study based on information entropy LF improved algorithm based on a combination of ant colony clustering algorithm strategy, the policy first use of the improved algorithm based on information entropy LF clustering process, and then based on the pheromone the K-means algorithm clustering results of post-optimization.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer software > Program design,software engineering > Programming > Database theory and systems
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