机构

• 地理科学与资源研究所 [2]
• 成都山地灾害与环境研... [1]
• 长春光学精密机械与物... [1]
• 武汉植物园 [1]
• 生态环境研究中心 [1]
• 西安光学精密机械研究... [1]
• 更多

采集方式

• OAI收割 [8]

内容类型

• 期刊论文 [6]
• SCI/SSCI论文 [1]
• 会议论文 [1]

发表日期

• 2024 [1]
• 2022 [1]
• 2017 [1]
• 2016 [1]
• 2015 [1]
• 2012 [1]
• 更多

学科主题

筛选

浏览/检索结果: 共8条，第1-8条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序作者升序作者降序 Source identification and risk assessment of trace metals in surface sediment of China Sea by combining APCA-MLR receptor model and lead isotope analysis 期刊论文  OAI收割 JOURNAL OF HAZARDOUS MATERIALS, 2024, 卷号: 465, 页码: 13 作者:  Zhou, Yanyan;  Du, Sen;  Liu, Yang;  Yang, Tao;  Liu, Yongliang   |  收藏  |  浏览/下载：17/0  |  提交时间：2024/10/28 China Sea  Sediment  Trace metals  APCS-MLR model  Pb isotope   Receptor model-based source apportionment and ecological risk of metals in sediments of an urban river in Bangladesh 期刊论文  OAI收割 JOURNAL OF HAZARDOUS MATERIALS, 2022, 卷号: 423, 页码: 15 作者:  Proshad, Ram;  Kormoker, Tapos;  Al, Mamun Abdullah;  Islam, Md Saiful;  Khadka, Sujan   |  收藏  |  浏览/下载：84/0  |  提交时间：2021/12/16 Toxic metals  Riverine sediments  PMF model  APCS-MLR model  Ecological risk   Using MLR to model the vertical error distribution of ASTER GDEM V2 data based on ICESat/GLA14 data in the Loess Plateau of China 期刊论文  OAI收割 ZEITSCHRIFT FUR GEOMORPHOLOGIE, 2017, 卷号: 61, 页码: 9-26 作者:  Zhao, Shangmin;  Cheng, Weiming;  Zhou, Chenghu;  Liu, Haijiang;  Su, Qiaomei   |  收藏  |  浏览/下载：93/0  |  提交时间：2019/05/30 vertical error distribution  MLR model  ASTER GDEM V2  ICESat/GLA14  land surface factors   Mapping soil organic matter concentration at different scales using a mixed geographically weighted regression method SCI/SSCI论文  OAI收割 2016 作者:  Zeng C. Y. 收藏  |  浏览/下载：62/0  |  提交时间：2016/12/16 Mixed geographically weighted regression (MGWR)  Geographically weighted  regression (GWR)  Multiple linear regression (MLR)  Soil organic matter  concentration (SOM)  multiple-linear-regression  spatial prediction  auxiliary information  carbon  variables  patterns  region  model  catchment  australia   Multiple linear regression model for bromate formation based on the survey data of source waters from geographically different regions across China 期刊论文  OAI收割 ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2015, 卷号: 22, 期号: 2, 页码: 1232-1239 作者:  Yu, Jianwei;  Liu, Juan;  An, Wei;  Wang, Yongjing;  Zhang, Junzhi 收藏  |  浏览/下载：18/0  |  提交时间：2016/03/11 Bromate formation potential  Ozonation  Alkalinity  Drinking water  MLR model   Multivariate Multilinear Regression 期刊论文  OAI收割 ieee transactions on systems man and cybernetics part b-cybernetics, 2012, 卷号: 42, 期号: 6, 页码: 1560-1573 作者:  Su, Ya;  Gao, Xinbo;  Li, Xuelong;  Tao, Dacheng 收藏  |  浏览/下载：32/0  |  提交时间：2013/07/01 Active appearance model (AAM)  multivariate linear regression (MLR)  principal component regression (PCR)  under sample problem (USP)   Response of dissolved trace metals to land use/land cover and their source apportionment using a receptor model in a subtropic river, China 期刊论文  OAI收割 JOURNAL OF HAZARDOUS MATERIALS, 2011, 卷号: 190, 期号: 1-3, 页码: 205-213 作者:  Li, Siyue;  Zhang, Quanfa   |  收藏  |  浏览/下载：22/0  |  提交时间：2017/04/13 Land use/land cover  Trace metals  Source apportionment  Multivariate statistic model  FA-MLR   Fast determination of total ginsenosides content in Ginseng powder by near infrared reflectance spectroscopy (EI CONFERENCE) 会议论文  OAI收割 ICO20: Biomedical Optics, August 21, 2005 - August 26, 2005, Changchun, China 作者:  Chen X.-D.;  Chen X.-D. 收藏  |  浏览/下载：29/0  |  提交时间：2013/03/25 Near infrared (NIR) reflectance spectroscopy was used to develop a fast determination method for total ginsenosides in Ginseng (Panax Ginseng) powder. The spectra were analyzed with multiplicative signal correction (MSC) correlation method. The best correlative spectra region with the total ginsenosides content was 1660 nm1880 nm and 2230nm-2380 nm. The NIR calibration models of ginsenosides were built with multiple linear regression (MLR)  principle component regression (PCR) and partial least squares (PLS) regression respectively. The results showed that the calibration model built with PLS combined with MSC and the optimal spectrum region was the best one. The correlation coefficient and the root mean square error of correction validation (RMSEC) of the best calibration model were 0.98 and 0.15% respectively. The optimal spectrum region for calibration was 1204nm-2014nm. The result suggested that using NIR to rapidly determinate the total ginsenosides content in ginseng powder were feasible.