发布求助
文献互助 智能选刊 最新文献

2009 IEEE International Conference on Granular Computing最新文献

筛选
英文 中文
Research on extracting conceptual frameworks of sentence groups 句子组概念框架提取方法研究
2009 IEEE International Conference on Granular Computing Pub Date : 2009-09-22 DOI: 10.1109/GRC.2009.5255054
Xiangfeng Wei, Jianming Miao, Quan Zhang
{"title":"Research on extracting conceptual frameworks of sentence groups","authors":"Xiangfeng Wei, Jianming Miao, Quan Zhang","doi":"10.1109/GRC.2009.5255054","DOIUrl":"https://doi.org/10.1109/GRC.2009.5255054","url":null,"abstract":"A sentence group is a processing unit between a sentence and a paragraph or an article. It is described with three aspects: domain, situation and background. Domain is the conceptual category of a sentence group. Situation is the conceptual framework of a sentence group. The conceptual framework of a sentence group is defined with several serial sentence categories (SCs), the semantic chunks in the SCs, and the conceptual restriction of those semantic chunks. Extracting the framework should base on the knowledge of domain sentence categories and then fill the framework with the right words or phrases in sentences, according to the SCs and semantic chunks. This paper introduces the description of conceptual frameworks of sentence groups. It also shows how to extract the elements in a framework based on analyzing the SCs of sentences. Finally, some aspects must be improved to reach a higher processing performance.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126689009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Machine learning as Granular Computing 作为颗粒计算的机器学习
2009 IEEE International Conference on Granular Computing Pub Date : 2009-09-22 DOI: 10.1109/GRC.2009.5255125
Hong Hu, Zhongzhi Shi
{"title":"Machine learning as Granular Computing","authors":"Hong Hu, Zhongzhi Shi","doi":"10.1109/GRC.2009.5255125","DOIUrl":"https://doi.org/10.1109/GRC.2009.5255125","url":null,"abstract":"Zadeh proposed that there are three basic concepts that underlie human cognition: granulation, organization and causation and a granule being a clump of points (objects) drawn together by indistinguishability, similarity, proximity or functionality. In this paper, we give out a novel definition of Granular Computing which can be easily treated by neural network. Perception learning as granular computing tries to study the machine learning from perception information sampling to dimensional reduction and samples classification in a granular way, and can be summaries as two kind approaches:(1) covering learning, (2) svm kind learning. We proved that although there are tremendous algorithms for dimensional reduction and information transformation, their ability can't transcend wavelet kind nested layered granular computing which are very easy for neural network processing.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"227 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130652319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 14
On structure of generalized intuitionistic fuzzy rough sets 广义直觉模糊粗糙集的结构
2009 IEEE International Conference on Granular Computing Pub Date : 2009-09-22 DOI: 10.1109/GRC.2009.5255087
Guilong Liu, Jie Liu
{"title":"On structure of generalized intuitionistic fuzzy rough sets","authors":"Guilong Liu, Jie Liu","doi":"10.1109/GRC.2009.5255087","DOIUrl":"https://doi.org/10.1109/GRC.2009.5255087","url":null,"abstract":"Intuitionistic fuzzy sets, originally proposed by Atanassov in 1986, are an attractive extension of fuzzy sets, which enriches the latter with extra features to represent uncertainty. The concept of IF rough sets comes from the combination of IF sets and rough sets. This paper studies axiomatic characterization of IF rough sets. The lower and upper approximations are respectively characterized by two simple axioms. We also consider lattice theoretical properties of IF rough sets and show that the set of all definable IF sets is a completely distributive lattice.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126535228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Ordered rules extraction for incomplete ordered decision system in granular computing 不完全有序决策系统的有序规则提取
2009 IEEE International Conference on Granular Computing Pub Date : 2009-09-22 DOI: 10.1109/GRC.2009.5255047
Jiucheng Xu, Jinling Shi, Wanli Cheng
{"title":"Ordered rules extraction for incomplete ordered decision system in granular computing","authors":"Jiucheng Xu, Jinling Shi, Wanli Cheng","doi":"10.1109/GRC.2009.5255047","DOIUrl":"https://doi.org/10.1109/GRC.2009.5255047","url":null,"abstract":"Granular computing is a new mathematic analysis method which deals with uncertain information, and it mainly solves problems from different information granularity layers. Aiming at incomplete ordered decision systems, this paper based on granular computing presents a new ordered rules extraction algorithm. Firstly, in order to effectively deal with the incomplete ordered decision system, we transform the incomplete ordered decision system into an extended order value decision table by defining the concept of extended order relation. Then, using the theory of granular computing, we introduce the definition of granular statement, λ-rank granular statement and λ-rank granular base in the extended order value decision table. Furthermore, with the search criteria for lowest limit of rule coverage and confidence satisfying user expectation, we design a new algorithm by analyzing the extended order value decision table and granular base from different granularity layers. The algorithm attempts to extract the ordered decision rules as more as possible from granular base in lower rank. Last, we give an application example for proving the validity of the algorithm.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131352562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Get what you want from Internet using fuzzy k-means clustering algorithm 使用模糊k-means聚类算法从互联网上得到你想要的
2009 IEEE International Conference on Granular Computing Pub Date : 2009-09-22 DOI: 10.1109/GRC.2009.5255009
De-Sheng Zhu, Ming-Qin Zhou
{"title":"Get what you want from Internet using fuzzy k-means clustering algorithm","authors":"De-Sheng Zhu, Ming-Qin Zhou","doi":"10.1109/GRC.2009.5255009","DOIUrl":"https://doi.org/10.1109/GRC.2009.5255009","url":null,"abstract":"This paper proposed a new method of getting what you want from Internet using fuzzy k-means clustering algorithm. It used search engine to obtain relevant documents content, then adopted efficient Fuzzy k-means clustering algorithm to cluster all the sentences. The summary sentences were extracted by turns from the clusters. Experimental result shows that the proposed method can improve the performance of summary.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132036660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Hybrid intelligent fault diagnosis based on granular computing 基于颗粒计算的混合智能故障诊断
2009 IEEE International Conference on Granular Computing Pub Date : 2009-09-22 DOI: 10.1109/GRC.2009.5255127
Zhaowen Hou, Zhousuo Zhang
{"title":"Hybrid intelligent fault diagnosis based on granular computing","authors":"Zhaowen Hou, Zhousuo Zhang","doi":"10.1109/GRC.2009.5255127","DOIUrl":"https://doi.org/10.1109/GRC.2009.5255127","url":null,"abstract":"To solve the problem of lacking hybrid modes and common algorithms in hybrid intelligent diagnosis, this paper presents a new approach to hybrid intelligent fault diagnosis of the mechanical equipment based on granular computing. The hybrid intelligent diagnosis model based on neighborhood rough set is constructed in different granular levels, and the results of support vector machines (SVMS) and artificial neural network (ANN) in granular levels are combined by criterion matrix algorithm as output of hybrid intelligent diagnosis. Finally, the proposed model is applied to fault diagnosis in roller bearings of high-speed locomotive. The applied results show that the classification accuracy of hybrid model reaches to 97.96%, which is 8.49% and 39.12% higher than the classification accuracy of SVMS and ANN respectively. It shows that the proposed model as a new common algorithm can reliably recognize different fault categories and effectively enhance robustness of the hybrid intelligent diagnosis model.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126575384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
When quadratic sorts use granules 二次排序时使用颗粒
2009 IEEE International Conference on Granular Computing Pub Date : 2009-09-22 DOI: 10.1109/GRC.2009.5255124
Jean-David Hsu
{"title":"When quadratic sorts use granules","authors":"Jean-David Hsu","doi":"10.1109/GRC.2009.5255124","DOIUrl":"https://doi.org/10.1109/GRC.2009.5255124","url":null,"abstract":"Quadratic sorting algorithms such as Selectionsort are valued for their simplicity, in-place property, and good performance on small input. On the other hand, a straightforward Mergesort is optimal, but has a linear space requirement. This paper explores the use of sorted granules built using Mergesort with bounded space requirement in order to increase the efficiency of an in-place stable quadratic sort.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"213 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117331348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Time consistency adjustment algorithm of time Petri Net 时间Petri网的时间一致性调整算法
2009 IEEE International Conference on Granular Computing Pub Date : 2009-09-22 DOI: 10.1109/GRC.2009.5255065
Jun Tong, Jian-min Han, Teng-fang Guo
{"title":"Time consistency adjustment algorithm of time Petri Net","authors":"Jun Tong, Jian-min Han, Teng-fang Guo","doi":"10.1109/GRC.2009.5255065","DOIUrl":"https://doi.org/10.1109/GRC.2009.5255065","url":null,"abstract":"Time Petri Net is an effective approach to modeling workflow. But existing modeling methods do not consider dynamic adjustment method for time consistency. This paper proposes two adjustment algorithms, CTAA for time consistency and ICTTA for time inconsistency. CTAA can improve the workflow efficiency and ICTAA can make the Petri Net capture the time consistency. We also propose a method to evaluate the time performance of Petri Net generated by CTAA based on granular computing. Finally, we give an instance to show the effectiveness of the proposed algorithms.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130957276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Clustering based-on indiscernibility and indiscernibility level 基于不可分辨性和不可分辨程度的聚类
2009 IEEE International Conference on Granular Computing Pub Date : 2009-09-22 DOI: 10.1109/GRC.2009.5255132
R. B. F. Hakim, Subanar, E. Winarko
{"title":"Clustering based-on indiscernibility and indiscernibility level","authors":"R. B. F. Hakim, Subanar, E. Winarko","doi":"10.1109/GRC.2009.5255132","DOIUrl":"https://doi.org/10.1109/GRC.2009.5255132","url":null,"abstract":"The core concept of classical rough sets are clustering similarities and dissimilarities of objects based on the notions of indiscernibility and discernibility. In this paper, we present a new method of clustering data based on the combination of indiscernibility and its indiscernibility level. The indiscernibility level quantifies the indiscernibility of pairs of objects among other objects in information systems. The result of this paper show the dual notions of indiscernibility and its indiscernibility level play an important role in clustering information systems.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133407609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
A framework for selecting salient features and samples simultaneously to enhance classifier performance 一个同时选择显著特征和样本以提高分类器性能的框架
2009 IEEE International Conference on Granular Computing Pub Date : 2009-09-22 DOI: 10.1109/GRC.2009.5255074
Dehong Qiu, Ye Wang, Qifeng Zhang
{"title":"A framework for selecting salient features and samples simultaneously to enhance classifier performance","authors":"Dehong Qiu, Ye Wang, Qifeng Zhang","doi":"10.1109/GRC.2009.5255074","DOIUrl":"https://doi.org/10.1109/GRC.2009.5255074","url":null,"abstract":"It is desirable to select out the salient subset of features and remove from the training set the instances that are not helpful to forming the final decision function of classifier. In present work we are trying to increase the classifier performance through efficiently selecting features and samples simultaneously. A new framework that coordinates feature selection and sample selection together is built. The criteria of optimal feature selection and the method of sample selection are designed. Using benchmark datasets, the effectiveness of the framework was tested in terms of their ability to raise the classifying correct rate while reducing the size of attribute set. Experimental results show that this new framework is effective and practical.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133221168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信