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基于組合核函數(shù)的秈稻重度不宜存檢測(cè)模型
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國(guó)家重大科技專項(xiàng)資助項(xiàng)目(4005-09500216)、中央高?;究蒲袠I(yè)務(wù)費(fèi)專項(xiàng)資助項(xiàng)目(2011PY038)和華中農(nóng)業(yè)大學(xué)科技創(chuàng)新基金(SRF)資助項(xiàng)目(2012029)


Identification Model of Severely Unstorable Indica Paddy Based on Combined Kernel Function
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    摘要:

    為給秈稻儲(chǔ)存品質(zhì)的判定提供一種快速無(wú)損檢測(cè)手段,對(duì)80份重度不宜存秈稻和80份非重度不宜存秈稻的近紅外反射光譜進(jìn)行了實(shí)驗(yàn)研究。根據(jù)訓(xùn)練樣本非線性可分的特點(diǎn),選擇支持向量機(jī)方法建立定性模型。在對(duì)不同核函數(shù)的特性進(jìn)行分析和研究的基礎(chǔ)上,定義了一種新的核函數(shù)——組合核函數(shù)。該組合核函數(shù)是多項(xiàng)式核函數(shù)與徑向基核函數(shù)的線性組合,將兩者各自的特點(diǎn)融合在一起兼具內(nèi)推和外推性能。實(shí)驗(yàn)結(jié)果表明,以這兩種函數(shù)的線性組合作為核函數(shù)且調(diào)節(jié)因子為0.7時(shí),所建立的模型綜合性能最好。所建模型的訓(xùn)練集正確識(shí)別率為97.21%,測(cè)試集正確識(shí)別率為93.25%。

    Abstract:

    In order to explore a rapid and non-destructive method for identifying storable quality of indica paddy, experiments were conducted on 80 samples of severely unstorable indica paddy and 80 samples of other indica paddy. Support vector machine (SVM) method was selected to build qualitative model according to training samples’ characteristics. A combined kernel function was defined after analyzing and studying different kernel function. The proposed combined kernel function was the linear combination of polynomial function and radial basis function, and it combined each advantage of these two functions to acquire both interpolation and extrapolation properties of kernel function. The experiments showed that the model had the best comprehensive performance when the linear combination polynomial function and radial basis function was taken as the kernel function of SVM, and the control factor was 0.7. The training identification rate was 97.21%,and the test identification rate was 93.25%.

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石禮娟,謝彪彪,謝新港,吳洋.基于組合核函數(shù)的秈稻重度不宜存檢測(cè)模型[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2013,44(8):165-168,194. Shi Lijuan, Xie Biaobiao, Xie Xin’gang, Wu Yang. Identification Model of Severely Unstorable Indica Paddy Based on Combined Kernel Function[J]. Transactions of the Chinese Society for Agricultural Machinery,2013,44(8):165-168,194.

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  • 在線發(fā)布日期: 2013-07-19
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