私密直播全婐app免费大渔直播,国产av成人无码免费视频,男女同房做爰全过程高潮,国产精品自产拍在线观看

相關鏈接
聯系方式
  • 通信地址:天津市西青區賓水西道399號天津工業大學化學與化工學院化學工程與工藝系6D518
  • 郵編:300387
  • 電話:022-83955663
  • 傳真:022-83955663
  • Email:bianxihui@163.com
當前位置:> 首頁 > 論文著作 > 正文
Variational mode decomposition weighted multiscale support vector regression for spectral determination of rapeseed oil and rhizoma alpiniae offcinarum adulterants
作者:Xihui Bian*, Deyun Wu, Kui Zhang, Peng Liu, Huibing Shi, Xiaoyao Tan, Zhigang Wang
關鍵字:Variational mode decomposition, Support vector regression, Adulteration, Quality control, Chemometrics
論文來源:期刊
具體來源:Biosensors, 2022, 12, 586
發表時間:2022年
    The accurate prediction of the model is essential for food and herb analysis. In order to exploit the abundance of information embedded in the frequency and time domains, a weighted multiscale support vector regression (SVR) method based on variational mode decomposition (VMD), namely VMD-WMSVR, was proposed for the ultraviolet-visible (UV-Vis) spectral determination of rapeseed oil adulterants and near-infrared (NIR) spectral quantification of rhizoma alpiniae offci narum adulterants. In this method, each spectrum is decomposed into K discrete mode components by VMD first. The mode matrix Uk is recombined from the decomposed components, and then, the SVR is used to build sub-models between each Uk and target value. The final prediction is obtained by integrating the predictions of the sub-models by weighted average. The performance of the proposed method was tested with two spectral datasets of adulterated vegetable oils and herbs. Compared with the results from partial least squares (PLS) and SVR, VMD-WMSVR shows potential in model accuracy.
主站蜘蛛池模板: 甘洛县| 巴彦县| 青海省| 延寿县| 宁乡县| 宣威市| 彭泽县| 隆林| 南丰县| 九龙城区| 昆山市| 礼泉县| 瑞金市| 珠海市| 乌审旗| 乌恰县| 新干县| 平遥县| 武鸣县| 贡觉县| 尚义县| 宜黄县| 仙游县| 长顺县| 射阳县| 绥德县| 西华县| 都匀市| 大荔县| 江西省| 姜堰市| 丹凤县| 邯郸市| 泰顺县| 五台县| 本溪市| 霍邱县| 海晏县| 陆丰市| 晋宁县| 微博|