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基于BPSO的棉花異性纖維目標(biāo)特征快速選擇方法
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國(guó)家自然科學(xué)基金資助項(xiàng)目（30971693）和新世紀(jì)優(yōu)秀人才計(jì)劃資助項(xiàng)目（NCET-09-0731）


A Fast Feature Selection for Cotton Foreign Fiber Objects Based on BPSO
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    摘要:

    針對(duì)現(xiàn)有棉花異性纖維目標(biāo)特征選擇方法迭代次數(shù)多、速度慢等問題，提出了一種基于改進(jìn)粒子群優(yōu)化算法的棉花異性纖維目標(biāo)特征快速選擇方法。使用離散型粒子群優(yōu)化算法作為特征選擇算法，利用支持向量機(jī)算法作為分類器對(duì)最優(yōu)特征集進(jìn)行驗(yàn)證。實(shí)驗(yàn)結(jié)果表明，在分類準(zhǔn)確率與蟻群算法相當(dāng)?shù)那闆r下，能減少26%的運(yùn)行時(shí)間。

    Abstract:

    A fast feature selection for cotton foreign fiber objects based on binary particle swarm optimization was presented, for the current feature selection of cotton foreign fiber having more iteration times and slow speed. Binary particle swarm optimization (BPSO) was used to select feature in the method, and the support vector machine algorithm was used to verify the optimal feature set. Experimental results showed that the running time could reduce by 26%, when the classification accuracy was almost with other algorithms.

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王金星,李恒斌,王蕊,劉雙喜,曹維時(shí),閆銀發(fā).基于BPSO的棉花異性纖維目標(biāo)特征快速選擇方法[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2013,44(2):188-191. Wang Jinxing, Li Hengbin, Wang Rui, Liu Shuangxi, Cao Weishi, Yan Yinfa. A Fast Feature Selection for Cotton Foreign Fiber Objects Based on BPSO[J]. Transactions of the Chinese Society for Agricultural Machinery,2013,44(2):188-191.

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  • 在線發(fā)布日期: 2013-02-04
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