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AN OPTIMIZATION GENETIC ALGORITHM FOR IMAGE DATABASES IN AGRICULTURE

机译:农业图像数据库的优化遗传算法

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摘要

Data Mining is rapidly evolving areas of research that are at the intersection of several disciplines, including statistics, databases, pattern recognition, and high-performance and parallel computing. In this paper, we propose a novel mining algorithm, called ARMAGA (Association rules mining Algorithm based on a novel Genetic Algorithm), to mine the association rules from an image database, where every image is represented by the ARMAGA representation. We first take advantage of the genetic algorithm designed specifically for discovering association rules. Second we propose the Algorithm Compared to the algorithm in, and the ARMAGA algorithm avoids generating impossible candidates, and therefore is more efficient in terms of the execution time.
机译:数据挖掘是快速发展的研究领域,处于统计学,数据库,模式识别以及高性能和并行计算等多个学科的交汇处。在本文中,我们提出了一种新颖的挖掘算法,称为ARMAGA(基于新型遗传算法的关联规则挖掘算法),用于从图像数据库中挖掘关联规则,其中每个图像均由ARMAGA表示表示。我们首先利用专门为发现关联规则而设计的遗传算法。其次,我们提出了与之相比的算法,ARMAGA算法避免了生成不可能的候选者,因此在执行时间方面更加高效。

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