本文選題：模糊支持向量機 + 隸屬度函數(shù)　； 參考：《武漢大學(xué)學(xué)報(信息科學(xué)版)》2017年04期

【摘要】：云類識別是實現(xiàn)衛(wèi)星云圖自動分析的基礎(chǔ),針對衛(wèi)星云圖易受噪聲干擾且不同云系往往相互交疊的特點,構(gòu)造一種面向云類識別的自適應(yīng)模糊支持向量機。該方法不僅改進了隸屬度函數(shù)的表現(xiàn)形式,而且通過定義控制臨界隸屬度和隸屬度衰減趨勢的參數(shù),使隸屬度能根據(jù)不同云系樣本的具體分布特性自適應(yīng)調(diào)整,解決了傳統(tǒng)模糊支持向量機的隸屬度函數(shù)難以反映樣本分布的問題。在MTSAT衛(wèi)星云圖上的實驗結(jié)果表明,通過提取云圖可見光通道的反照率、紅外通道的亮溫及三種亮溫差作為云圖的光譜特征,并結(jié)合統(tǒng)計紋理特征,所構(gòu)造的自適應(yīng)模糊支持向量機分類器能有效區(qū)分晴空區(qū)、低云、中云、高云及直展云;云類識別準確率優(yōu)于標準支持向量機和傳統(tǒng)模糊支持向量機,且具有更強的穩(wěn)定性和自適應(yīng)性。
[Abstract]:Cloud recognition is the basis of automatic analysis of satellite cloud images. In view of the characteristics that satellite cloud images are susceptible to noise interference and different cloud systems often overlap with each other, an adaptive fuzzy support vector machine for cloud recognition is constructed. This method not only improves the form of membership function, but also adaptively adjusts membership according to the specific distribution characteristics of different cloud samples by defining the parameters controlling the critical membership and the attenuation trend of membership. It solves the problem that the membership function of traditional fuzzy support vector machine can not reflect the distribution of samples. The experimental results on MTSAT satellite cloud images show that by extracting the albedo of visible light channels of cloud images, the brightness temperature of infrared channels and three kinds of bright temperature differences are taken as spectral features of cloud images, and combined with statistical texture features, The adaptive fuzzy support vector machine classifier can effectively distinguish clear sky region, low cloud, middle cloud, Gao Yun and straight cloud, and the accuracy of cloud recognition is better than that of standard support vector machine and traditional fuzzy support vector machine. And has stronger stability and self-adaptability.
【作者單位】： 寧波大學(xué)信息科學(xué)與工程學(xué)院;
【基金】：國家自然科學(xué)基金(61271399,61471212) 寧波市國際合作項目(2013D10011) 寧波市自然科學(xué)基金(2011A610192,2013A610055) 浙江省信息與通信工程重中之重學(xué)科項目(XKXL1425,XKXL1306)~~
【分類號】：TP391.41;TP18

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本文編號：1953607