机构

• 地理科学与资源研究所 [1]
• 长春光学精密机械与物... [1]
• 上海药物研究所 [1]
• 沈阳自动化研究所 [1]
• 生态环境研究中心 [1]
• 西安光学精密机械研究... [1]
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采集方式

• OAI收割 [6]

内容类型

• 期刊论文 [4]
• 会议论文 [2]

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• 2022 [1]
• 2015 [1]
• 2014 [1]
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浏览/检索结果: 共6条，第1-6条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 A Star-Identification Algorithm Based on Global Multi-Triangle Voting 期刊论文  OAI收割 APPLIED SCIENCES-BASEL, 2022, 卷号: 12, 期号: 19 作者:  Yuan, Xiaobin;  Zhu, Jingping;  Zhu, Kaijian;  Li, Xiaobin   |  收藏  |  浏览/下载：48/0  |  提交时间：2022/10/25 star identification  feature unit voting  two-dimension lookup table  principal component analysis (PCA)  largest cluster method   Improved Chromatographic Fingerprinting Combined with Multi-components Quantitative Analysis for Quality Evaluation of Penthorum chinense by UHPLC-DAD 期刊论文  OAI收割 NATURAL PRODUCT COMMUNICATIONS, 2015, 卷号: 10, 期号: 1, 页码: 71-76 作者:  Deng, Wangping;  Xu, Tongtong;  Yang, Min   |  收藏  |  浏览/下载：20/0  |  提交时间：2019/01/08 Penthoruni chinense Pursh  UHPLC  Fingerprint  Multi-components quantitative analysis  Method validation  Similarity  PCA   Optimized basis function for spectral reflectance recovery from tristimulus values 期刊论文  OAI收割 Optical Review, 2014, 卷号: 21, 期号: 2, 页码: 117-126 作者:   收藏  |  浏览/下载：36/0  |  提交时间：2014/05/14 basis function  reflectance spectra recovery  multi-object optimization  PCA method  genetic algorithm  tristimulus values   An improved hyperspectral classification algorithm based on back-propagation neural networks (EI CONFERENCE) 会议论文  OAI收割 2012 2nd International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2012, June 1, 2012 - June 3, 2012, Nanjing, China 作者:  Yu P.;  Yu P. 收藏  |  浏览/下载：34/0  |  提交时间：2013/03/25 In this paper  a new method is proposed to improve the classification performance of hyperspectral images by combining the principal component analysis (PCA)  genetic algorithm (GA)  and artificial neural networks (ANNs). First  some characteristics of the hyperspectral remotely sensed data  such as high correlation  high redundancy  etc.  are investigated. Based on the above analysis  we propose to use the principal component analysis to capture the main information existing in the hyperspectral images and reduce its dimensionality consequently. Next  we use neural networks to classify the reduced hyperspectral data. Since the back-propagation neural network we used is easy to suffer from the local minimum problem  we adopt a genetic algorithm to optimize the BP network's weights and the threshold. Experimental results show that the classification accuracy is improved and the time of calculation is reduced as well. 2012 IEEE.   Spatial prediction of soil moisture content using multiple-linear regressions in a gully catchment of the Loess Plateau, China 期刊论文  OAI收割 JOURNAL OF ARID ENVIRONMENTS, 2010, 卷号: 74, 期号: 2, 页码: 208-220 Qiu, Y.; Fu, B.; Wang, J.; Chen, L.; Meng, Q.; Zhang, Y. 收藏  |  浏览/下载：37/0  |  提交时间：2015/07/30 DCA  Enter-method regression  Land use type  Model evaluation measures  PCA  Stepwise-method regression  Topographical indices   Chaotic analysis on monthly precipitation on hills region in middle SiChuan, China 会议论文  OAI收割 Men B. H. 收藏  |  浏览/下载：17/0  |  提交时间：2012/06/30 correlation dimension  hills region in middle of SiChuan  principal  component analysis (PCA) method  kolmogorov entropy  time-series  deterministic chaos  strange attractors  river flow  rainfall  nonlinearity  redundancies  storm