亚洲一区欧美在线,日韩欧美视频免费观看,色戒的三场床戏分别是在几段,欧美日韩国产在线人成

基于流形學(xué)習(xí)算法的柑橘葉片氮含量光譜估測模型
作者:
作者單位:

作者簡介:

通訊作者:

中圖分類號:

基金項(xiàng)目:

國家自然科學(xué)基金資助項(xiàng)目(30871450)、廣東省自然科學(xué)基金資助項(xiàng)目(S2012010009856)和廣州市科技計(jì)劃資助項(xiàng)目


Estimation Model of Nitrogen Content for Citrus Leaves by SpectralTechnology Based on Manifold Learning Algorithm
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 圖/表
  • |
  • 訪問統(tǒng)計(jì)
  • |
  • 參考文獻(xiàn)
  • |
  • 相似文獻(xiàn)
  • |
  • 引證文獻(xiàn)
  • |
  • 資源附件
  • |
  • 文章評論
    摘要:

    提出了一種基于流形學(xué)習(xí)算法的柑橘葉片氮含量光譜快速檢測方法。分別在萌芽期、穩(wěn)果期、壯果促梢期和采果期,使用ASD FieldSpec 3光譜儀采集了柑橘葉片的反射光譜,并同步采用凱式定氮法測定葉片的氮含量。首先采用正交試驗(yàn)確定各個(gè)生長期小波去噪的最佳參數(shù)組合,然后分別采用主成分分析、多維尺度變換、局部線性嵌入、等距映射和拉普拉斯特征映射5種流形學(xué)習(xí)算法對原始光譜和經(jīng)小波去噪后的光譜數(shù)據(jù)進(jìn)行特征提取,將特征數(shù)據(jù)導(dǎo)入支持向量機(jī)回歸建立柑橘葉片氮含量預(yù)測模型,4個(gè)生長期的最佳驗(yàn)證集模型決定系數(shù)依次為0.9014、0.9344、0.8954和0.8779。試驗(yàn)結(jié)果表明,這5種流形學(xué)習(xí)算法都能有效地用于柑橘葉片氮含量預(yù)測,為柑橘葉片氮含量快速無損檢測、生長態(tài)勢監(jiān)測和變量施肥提供了理論依據(jù)。

    Abstract:

    Traditional methods of obtaining nitrogen content of citrus leaves are time-consuming, and the process is cumbersome and harmful to citrus leaves, which need proficient experiment techniques and amounts of instruments, equipment and chemical reagents. According to the high dimensionality and redundancy of origin spectral reflectance, a nitrogen content obtaining method of citrus leaves was provided based on manifold learning algorithm which was applied to the high-dimensional spectral vectors for dimension reduction and feature extraction. During four different growth stages, corresponding to germination, stability, bloom and picking stages, spectral reflectance of citrus leaves were measured by the ASD FieldSpec 3 spectrometer, respectively, and at the same time, nitrogen content of citrus leaves was obtained by using Kjeldahl method. For data processing, firstly the parameter combination of wavelet denoising which was used to the high-frequency noise removal was optimized through orthogonal test, and then the principal component analysis (PCA), multidimensional scaling (MDS), locally-linear embedding (LLE), isometric mapping (Isomap) and laplacian eigenmaps (LE) manifold learning algorithms were applied to extract features of original spectrum and denoised spectrum. Finally, the five corresponding support vector regression (SVR) prediction models of nitrogen content for citrus leaves were established based on their features. Experiment results reveal that the five manifold learning algorithms can be effectively used to predict nitrogen content of citrus leaves, which provides theoretical basis for obtaining nitrogen content of citrus leaves rapidly and non-destructively, as well as in growth monitoring and variable-rate fertilization.

    參考文獻(xiàn)
    相似文獻(xiàn)
    引證文獻(xiàn)
引用本文

岳學(xué)軍,全東平,洪添勝,劉永鑫,吳慕春,段潔利.基于流形學(xué)習(xí)算法的柑橘葉片氮含量光譜估測模型[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2015,46(6):244-250. Yue Xuejun, Quan Dongping, Hong Tiansheng, Liu Yongxin, Wu Muchun, Duan Jieli. Estimation Model of Nitrogen Content for Citrus Leaves by SpectralTechnology Based on Manifold Learning Algorithm[J]. Transactions of the Chinese Society for Agricultural Machinery,2015,46(6):244-250.

復(fù)制
分享
文章指標(biāo)
  • 點(diǎn)擊次數(shù):
  • 下載次數(shù):
  • HTML閱讀次數(shù):
  • 引用次數(shù):
歷史
  • 收稿日期:2015-01-19
  • 最后修改日期:
  • 錄用日期:
  • 在線發(fā)布日期: 2015-06-10
  • 出版日期: 2015-06-10