机构

• 自动化研究所 [3]
• 重庆绿色智能技术研究... [2]
• 沈阳应用生态研究所 [2]
• 沈阳自动化研究所 [2]
• 计算技术研究所 [1]
• 长春光学精密机械与物... [1]
• 更多

采集方式

• OAI收割 [11]

内容类型

• 期刊论文 [8]
• 会议论文 [3]

发表日期

• 2022 [1]
• 2021 [2]
• 2020 [2]
• 2018 [1]
• 2017 [1]
• 2015 [1]
• 更多

学科主题

• Forestry [2]

筛选

浏览/检索结果: 共11条，第1-10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 A Data-Characteristic-Aware Latent Factor Model for Web Services QoS Prediction 期刊论文  OAI收割 IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2022, 卷号: 34, 期号: 6, 页码: 2525-2538 作者:  Wu, Di;  Luo, Xin;  Shang, Mingsheng;  He, Yi;  Wang, Guoyin   |  收藏  |  浏览/下载：63/0  |  提交时间：2022/08/22 Web Service  quality-of-service  QoS  latent factor analysis  density peak  data-characteristic-aware  missing data  big data  topological neighborhood  noise data  service selection  data science   A Novel Approximate Spectral Clustering Algorithm With Dense Cores and Density Peaks 期刊论文  OAI收割 IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 页码: 13 作者:  Cheng, Dongdong;  Huang, Jinlong;  Zhang, Sulan;  Zhang, Xiaohua;  Luo, Xin   |  收藏  |  浏览/下载：32/0  |  提交时间：2022/08/22 Clustering algorithms  Manifolds  Matrix decomposition  Sparse matrices  Partitioning algorithms  Approximation algorithms  Level measurement  Approximate spectral clustering  common neighborhood-based distance  dense cores  density peaks  geodesic distance   Remote sensing analysis of oilfield IoT based on density clustering 会议论文  OAI收割 Shenyang, China, November 8-11, 2021 作者:  Zhang T(张涛);  Fu DZ(付殿峥);  Xu YY(许原野);  Dong JY(董静雅)   |  收藏  |  浏览/下载：91/0  |  提交时间：2021/12/13 Internet of Things  Data mining  Density clustering  Density peaks  Neighborhood   Multi-feature weighting neighborhood density clustering 期刊论文  OAI收割 NEURAL COMPUTING & APPLICATIONS, 2020, 卷号: 32, 期号: 13, 页码: 9545-9565 作者:  Xu, Shuliang;  Feng, Lin;  Liu, Shenglan;  Zhou, Jian;  Qiao, Hong   |  收藏  |  浏览/下载：43/0  |  提交时间：2020/08/03 Clustering analysis  Multi-feature  Neighborhood density  Rough set  Granular computing   Anomaly Detection Using Local Kernel Density Estimation and Context-Based Regression 期刊论文  OAI收割 IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2020, 卷号: 32, 期号: 2, 页码: 218-233 作者:  Hu, Weiming;  Gao, Jun;  Li, Bing;  Wu, Ou;  Du, Junping   |  收藏  |  浏览/下载：51/0  |  提交时间：2020/03/30 Anomaly detection  Kernel  Estimation  Saliency detection  Visualization  Data models  Computational modeling  Anomaly detection  local kernel density estimation  weighted neighborhood density  hierarchical context-based local kernel regression   A robust density peaks clustering algorithm using fuzzy neighborhood 期刊论文  OAI收割 INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, 2018, 卷号: 9, 期号: 7, 页码: 1131-1140 作者:  Du, Mingjing;  Ding, Shifei;  Xue, Yu   |  收藏  |  浏览/下载：41/0  |  提交时间：2019/12/10 Clustering analysis  Density peaks clustering  Fuzzy joint points  Fuzzy neighborhood relation   An Effective Density Based Approach to Detect Complex Data Clusters Using Notion of Neighborhood Difference 期刊论文  OAI收割 International Journal of Automation and Computing, 2017, 卷号: 14, 期号: 1, 页码: 57-67 作者:  S. Nagaraju;  Manish Kashyap;  Mahua Bhattachraya   |  收藏  |  浏览/下载：22/0  |  提交时间：2021/02/23 Density based clustering  neighborhood difference  density-based spatial clustering of applications with noise (DBSCAN)  space density indexing (SDI)  core object.   An optimized initialization center K-means clustering algorithm based on density 会议论文  OAI收割 2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), Shenyang, China, June 8-12, 2015 作者:  Yuan QL(袁启龙);  Shi HB(史海波);  Zhou XF(周晓锋) 收藏  |  浏览/下载：54/0  |  提交时间：2016/04/30 Clustering  K-means Algorithm  Initial Center Points  Neighborhood Density Distance   Eight-neighborhood based background modeling (EI CONFERENCE) 会议论文  OAI收割 2012 2nd International Conference on Materials Science and Information Technology, MSIT 2012, August 24, 2012 - August 26, 2012, Xi'an, Shaan, China Yan L.; Ming D.; Lei J. 收藏  |  浏览/下载：26/0  |  提交时间：2013/03/25 In order to solve the Gaussian kernel density-based background modeling  we propose a background modeling method based on an 8-neighborhood pixels sample set. In this method  we use the target pixel and its surrounding 8-neighborhood pixels to analyze whether it is included in the background or in the foreground sample space. Experimental results show that the method can judge the object as the background interference caused by the cyclical movement. By practical verification  the algorithm of the background modeling can full meet the requirements of the target detection algorithm. (2012) Trans Tech Publications  Switzerland.   Density dependence on tree survival in an old-growth temperate forest in northeastern China 期刊论文  OAI收割 ANNALS OF FOREST SCIENCE, 2009, 卷号: 66, 期号: 2, 页码: - 作者:  Zhang, J;  Hao, ZQ;  Sun, IF;  Song, B;  Ye, J   |  收藏  |  浏览/下载：42/0  |  提交时间：2011/09/23 Competition  Density-dependent Mortality  Neighborhood Effects  Spatial Pattern Analysis  Temperate Forest