Research of feature selection of red cell and white cell of urinary sediment images based on genetic algorithm embedded with multi-criteria

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Communication Engineering College, Chongqing University, Chongqing 400030, China [1 ]
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Xitong Fangzhen Xuebao | 2008年 / 14卷 / 3853-3857+3863期
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Based on the feature selection issue of red cells and white cells, one new method (NMGA) for it was proposed. That is: according to the feature selection about red cells and white cells, the modified genetic algorithm was adopted to deal with it. The modified genetic algorithm used gene-fixing technology (gradually fix the features during several generations), and combined the Niche technology together to enhance the performance of the genetic algorithm. Besides, voting mechanism was introduced with multi-criteria during each evolution operation. The effect of these experiments show that this algorithm performs better than simple genetic algorithm SGA , the features are reduced by this algorithm, and the complexity of the classifier is reduced apparently.
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