位置：成果数据库 > 会议 > 会议详情页
第八届中国Rough集与软计算学术会议、第二届中国web智能学术研讨会、第二届中国粒计算学术研讨会联合会议（CRSSC-CGrC-CWI 2008）论文集
  • 所属机构名称：重庆邮电大学
  • 会议名称：第八届中国Rough集与软计算学术会议、第二届中国web智能学术研讨会、第二届中国粒计算学术研讨会联合会议（CRSSC-CGrC-CWI 2008）论文集
  • 成果类型：会议
  • 相关项目：基于粒计算的海量数据挖掘理论与高效算法研究
同会议论文项目
基于粒计算的海量数据挖掘理论与高效算法研究
期刊论文 42 会议论文 38 著作 2
同项目会议论文
第七届中国Rough集与软计算学术会议、第一届中国web智能学术研讨会、第一届中国粒计算学术研讨会联合会议（CRSSC-CGrC-CWI 2007）论文集
Introduction to 3DM: Domain-Oriented Data-Driven Data Mining
Solving the Attribute Reduction Problem with Ant Colony Optimization
Similarity Measure of Vague Sets
Quick Knowledge Reduction Based on Devide and Conquer Method in Huge Data Sets
Domain-Oriented Data-Driven Data Mining (3DM): Simulation of Human Knowledge Understanding
基于商空间的概念聚类算法
Research on System Uncertainty Measures Based on Rough Set Theory
Fast Knowledge Reduction Algorithms Based on Quick Sort
Granular Computing Based Data Mining in the Views of Rough Set and Fuzzy Set
Domain-Oriented Data-Driven Data Mining Based on Rough Set
A General Model for Transforming Vague Sets into Fuzzy Sets
Facial Expression Recognition Based on Rough Sets Theory and SVM
Knowledge Acquisition in Vague Objective Information Systems
Approximation Partition Spaces of Covering Space
基于粗糙集理论的双模情感识别
Fast Knowledge Reduction Based on Quick Sort
基于自动阈值的不完备信息系统处理（摘要）
An Audiovisual Emotion Recognition System Based on Rough Set Theory
集值信息系统中的粗糙集扩展模型（摘要）
一种基于粗糙集理论的快速并行属性约简算法（摘要）
An Approach for Selective Ensemble Feature Selection Based on Rough Set Theory
Attribute Reduction Based on Granular Computing
A Self-Learning Model Based on Granular Computing
Uncertainty Measure of Covering Generated Rough Set
Incomplete Information Systems Processing Based on Fuzzy-clustering
Knowledge Acquisition in Vague Information Systems
IEEE第五届认知信息学国际学术会议杰出组织奖
第六届中国Rough集与软计算学术研讨会论文集
Domain-oriented Data-driven Data Mining: a New Understanding for Data Mining
分层递阶的模糊商空间结构分析
基于一般关系的Rough近似算子的研究
Quick Building of Fuzzy Equivalence Matrix in Granular Computing
A Data Driven Emotion Recognition Method Based on Rough Set Theory
Huge Data Mining Based on Rough Set Theory and Granular Computing
Attribute Core Computation Based on Divide and Conquer Method
Knowledge Reduction of Covering Approximation Space