• Complex
  • Title
  • Keyword
  • Abstract
  • Scholars
  • Journal
  • ISSN
  • Conference
成果搜索
High Impact Results & Cited Count Trend for Year Keyword Cloud and Partner Relationship
Sort by:
Default
  • Default
  • Title
  • Year
  • WOS Cited Count
  • Impact factor
  • Ascending
  • Descending
< Page ,Total 1 >
基于干扰管理理论的鲜活农产品路径优化研究
期刊论文 | 2015 , (11) , 189-190 | 物流工程与管理
Abstract&Keyword Cite

Abstract :

干扰发生后,对原配送方案产生影响,从顾客、驾驶员、配送方三方面进行扰动度量,建立基于干扰管理理论的鲜活农产品路径优化模型,进行配送路径的再次优化。

Keyword :

干扰管理 干扰管理 扰动度量 扰动度量 路径优化 路径优化

Cite:

Copy from the list or Export to your reference management。

GB/T 7714 向思雯 , 王述云 . 基于干扰管理理论的鲜活农产品路径优化研究 [J]. | 物流工程与管理 , 2015 , (11) : 189-190 .
MLA 向思雯 等. "基于干扰管理理论的鲜活农产品路径优化研究" . | 物流工程与管理 11 (2015) : 189-190 .
APA 向思雯 , 王述云 . 基于干扰管理理论的鲜活农产品路径优化研究 . | 物流工程与管理 , 2015 , (11) , 189-190 .
Export to NoteExpress RIS BibTex

Version :

基于距离与熵的混合属性数据流聚类算法 CSCD PKU
期刊论文 | 2010 , 31 (12) , 2365-2371 | 小型微型计算机系统
Abstract&Keyword Cite

Abstract :

针对越来越多的应用领域要求数据流聚类算法能处理同时包含数值属性特征与分类属性特征的数据,同时由于在已有的流数据聚类算法中,大多只针对单一数据类型的聚类,为此,提出混合属性数据流聚类算法.该算法在聚类分析过程中,同时利用数值属性与分类属性来定义聚类对象问的相异性,保存了对象的完整信息,使得聚类结果更能真实反映数据流中数据的分布情况.实验结果表明,该算法具有良好的聚类质量及较快的数据处理能力,同时具有良好的可扩展性.

Keyword :

数据流 数据流 混合属性 混合属性 聚类 聚类

Cite:

Copy from the list or Export to your reference management。

GB/T 7714 王述云 , 胡运发 , 范颖捷 et al. 基于距离与熵的混合属性数据流聚类算法 [J]. | 小型微型计算机系统 , 2010 , 31 (12) : 2365-2371 .
MLA 王述云 et al. "基于距离与熵的混合属性数据流聚类算法" . | 小型微型计算机系统 31 . 12 (2010) : 2365-2371 .
APA 王述云 , 胡运发 , 范颖捷 , 徐和祥 . 基于距离与熵的混合属性数据流聚类算法 . | 小型微型计算机系统 , 2010 , 31 (12) , 2365-2371 .
Export to NoteExpress RIS BibTex

Version :

Data stream clustering based on immune principle EI CSCD PKU
期刊论文 | 2009 , 22 (2) , 246-255 | Pattern Recognition and Artificial Intelligence
Abstract&Keyword Cite

Abstract :

The learning based on immune principle adapts well to the dynamic environment, and thus it can be applied to the data stream processing which is dynamic and requires high-speed processing. Therefore, an algorithm of clustering data streams based on immune principle is proposed, namely AIN-STREAM. The proposed algorithm can track the evolving clusters on noisy data sets. AIN-STREAM is capable of adjusting the recognition zone of B-cells automatically according to the requirement of users by creating and maintaining the B-Cell feature vectors. Thus, the stability of the clustering result is ensured. Theoretical analysis and comprehensive experimental results demonstrate that AIN-STREAM is superior over other immune principle based clustering algorithms under the circumstance of similar clustering results. Moreover, the results show that AIN-STREAM has a high clustering quality.

Keyword :

Clustering algorithms Clustering algorithms Data streams Data streams High speed cameras High speed cameras

Cite:

Copy from the list or Export to your reference management。

GB/T 7714 Wang, Shu-Yun , Zhang, Cheng-Hong , Hao, Xiu-Lan et al. Data stream clustering based on immune principle [J]. | Pattern Recognition and Artificial Intelligence , 2009 , 22 (2) : 246-255 .
MLA Wang, Shu-Yun et al. "Data stream clustering based on immune principle" . | Pattern Recognition and Artificial Intelligence 22 . 2 (2009) : 246-255 .
APA Wang, Shu-Yun , Zhang, Cheng-Hong , Hao, Xiu-Lan , Hu, Yun-Fa . Data stream clustering based on immune principle . | Pattern Recognition and Artificial Intelligence , 2009 , 22 (2) , 246-255 .
Export to NoteExpress RIS BibTex

Version :

10| 20| 50 per page
< Page ,Total 1 >

Export

Results:

Selected

to

Format:
Online/Total:918/7276432
Address:FZU Library(No.2 Xuyuan Road, Fuzhou, Fujian, PRC Post Code:350116) Contact Us:0591-22865326
Copyright:FZU Library Technical Support:Beijing Aegean Software Co., Ltd. 闽ICP备05005463号-1