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2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery最新文献

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Mining Positive and Negative Fuzzy Sequential Patterns in Large Transaction Databases 大型事务数据库中正负模糊序列模式的挖掘
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Pub Date : 2008-11-05 DOI: 10.1109/FSKD.2008.245
Weimin Ouyang, Qinhua Huang, Shuanghu Luo
{"title":"Mining Positive and Negative Fuzzy Sequential Patterns in Large Transaction Databases","authors":"Weimin Ouyang, Qinhua Huang, Shuanghu Luo","doi":"10.1109/FSKD.2008.245","DOIUrl":"https://doi.org/10.1109/FSKD.2008.245","url":null,"abstract":"Sequential patterns mining is an important research topic in data mining and knowledge discovery. Traditional algorithms for mining sequential patterns are built on the binary attributes databases, which has two limitations. First, it can not concern quantitative attributes; second, only positive sequential patterns are discovered. Mining fuzzy sequential patterns has been proposed to address the first limitation. In this paper, we put forward a discovery algorithm for mining negative sequential patterns to resolve the second limitation, and a discovery algorithm for mining both positive and negative fuzzy sequential patterns by combining these two approaches.","PeriodicalId":208332,"journal":{"name":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127948952","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: 11
Fuzzy Reliability Analysis of a Multi-sensor Fusion System 多传感器融合系统的模糊可靠性分析
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Pub Date : 2008-10-18 DOI: 10.1109/FSKD.2008.501
Minghua Jiang, Ming Hu, Tao Peng, Y. Ding
{"title":"Fuzzy Reliability Analysis of a Multi-sensor Fusion System","authors":"Minghua Jiang, Ming Hu, Tao Peng, Y. Ding","doi":"10.1109/FSKD.2008.501","DOIUrl":"https://doi.org/10.1109/FSKD.2008.501","url":null,"abstract":"Reliability models for various fault tolerant computer architectures are developed. Markov model is very useful calculating with state space by using transition probability and initial value. In practice, sometimes we can not have the exact values of lambda, mu, rho but with some uncertainty about these values. The combination fuzzy logic and Markov model method is introduced and analyzed besides the traditionally used reliability measures such as multi-sensor system reliability. This reliability model is a technique for analyzing fault tolerant designs under considerable uncertainty, such as the component failure rates. The presented model provides the estimation of the lower and upper boundary of multi-sensor fusion system with a single run of the model.","PeriodicalId":208332,"journal":{"name":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115151968","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: 2
The Qualitative Spatial Reasoning to Mechanical Configuration 力学构型的定性空间推理
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Pub Date : 2008-10-18 DOI: 10.1109/FSKD.2008.590
H. Feng, C. Shao, Yi Xu
{"title":"The Qualitative Spatial Reasoning to Mechanical Configuration","authors":"H. Feng, C. Shao, Yi Xu","doi":"10.1109/FSKD.2008.590","DOIUrl":"https://doi.org/10.1109/FSKD.2008.590","url":null,"abstract":"A qualitative reasoning approach is used for the spatial configuration of mechanisms in conceptual design phase. The appropriate types of mechanisms are chosen firstly for a specific reasoning task. The qualitative vectors of the basic components are given to construct the complicated mechanism. Based on the qualitative sign algebra rules, the reasoning algorithm is presented to reason the spatial configuration of the selected mechanism. The static reasoning process of the mechanism structure in-side a truck is shown finally, which indicates that the qualitative reasoning can be an assistant method when the numeric information is incomplete.","PeriodicalId":208332,"journal":{"name":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115397965","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: 2
Dealing with Complexity in Large Scale and Structured Fuzzy Systems 处理大规模和结构化模糊系统的复杂性
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Pub Date : 2008-10-18 DOI: 10.1109/FSKD.2008.342
C. García-Alonso
{"title":"Dealing with Complexity in Large Scale and Structured Fuzzy Systems","authors":"C. García-Alonso","doi":"10.1109/FSKD.2008.342","DOIUrl":"https://doi.org/10.1109/FSKD.2008.342","url":null,"abstract":"Fuzzy inference engines must always deal with the complexity involved in an exponentially increasing number of rules. Sometimes in complex problems, it is difficult to have expert knowledge at onepsilas disposal to design the whole rule set. Nevertheless, experts can guide the rule design by defining the variables involved and giving guidelines about their behavior. A dependence relationship (DR) is a set of rules defined by a group of related inputs and outputs. In order to make the design and evaluation of DRs automatic, two properties called type and intensity are introduced. The DR type identifies the output membership functions shifting the neutral selection to the right or to the left. The DR intensity qualifies the final output membership function selection admitting the existence of nuances in rule fulfillment. Applying these properties, DR rules can be automatically designed and appropriately interpreted by the fuzzy inference engine in complex systems.","PeriodicalId":208332,"journal":{"name":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115735399","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: 6
An Email Classification Model Based on Rough Set and Support Vector Machine 基于粗糙集和支持向量机的电子邮件分类模型
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Pub Date : 2008-10-18 DOI: 10.1109/FSKD.2008.658
Zhiqing Zhu
{"title":"An Email Classification Model Based on Rough Set and Support Vector Machine","authors":"Zhiqing Zhu","doi":"10.1109/FSKD.2008.658","DOIUrl":"https://doi.org/10.1109/FSKD.2008.658","url":null,"abstract":"The communication via email is one of the most popular services of the Internet. Emails have brought us great convenience in our daily work and life. However, unsolicited messages or spam, flood our email boxes, which results in bandwidth, time and money wasting. To this end, this paper presents a novel approach based on rough set theory and supporter vector machine is proposed to classify emails. The experiment results show this approach can get high recognition ratio and reduce the cost of calculation.","PeriodicalId":208332,"journal":{"name":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125231674","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: 16
Effective Schema Extraction of Query Interfaces on the Deep Web 深度Web查询接口的有效模式提取
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Pub Date : 2008-10-18 DOI: 10.1109/FSKD.2008.135
Bao-hua Qiang, Jian-qing Xi, Ling Chen
{"title":"Effective Schema Extraction of Query Interfaces on the Deep Web","authors":"Bao-hua Qiang, Jian-qing Xi, Ling Chen","doi":"10.1109/FSKD.2008.135","DOIUrl":"https://doi.org/10.1109/FSKD.2008.135","url":null,"abstract":"The Deep Web is becoming a very important information resource. Unlike the traditional Web information retrieval, the contents on the Deep Web are only accessible through source query interfaces. However, for any domain of interest, there may be so many query interfaces that users need to access them in order to get the desired information, which is time-consuming and requires to build an integrated query interface over the sources. The first important task towards this goal is schema extraction of source query interface. In this paper, we will present a novel pre-clustering algorithm with proper grouping patterns to obtain partial clustering of attributes. Our approach can avoid obtaining the incorrect subsets when grouping attributes. The experimental results showed our approach is highly effective on schema extraction of source query interfaces on the Deep Web.","PeriodicalId":208332,"journal":{"name":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116927507","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: 9
Fuzzy-Set Based Fast Edge Detection of Medical Image 基于模糊集的医学图像快速边缘检测
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Pub Date : 2008-10-18 DOI: 10.1109/FSKD.2008.431
Yanjun Zeng, C. Tu, Xiaojun Zhang
{"title":"Fuzzy-Set Based Fast Edge Detection of Medical Image","authors":"Yanjun Zeng, C. Tu, Xiaojun Zhang","doi":"10.1109/FSKD.2008.431","DOIUrl":"https://doi.org/10.1109/FSKD.2008.431","url":null,"abstract":"A fast edge detection method basing on the combination of fuzzy subsets is developed, while the detection of an edge as a classification problem will be considered, partitioning the image into two portions: the edge portion and the non-edge portion. The latter one, as the main constituent of an image, consists of the object and its background. Removing the non-edge portion from an image, the remainder is nothing but the edge of this image. In this paper, the gray level histogram is partitioned into several sub-regions, and some operations are performed with the associated fuzzy subsets corresponding to those sub-edges in the sub-regions on the gray-level-square-difference histogram, and the edge of this image is finally obtained. Practical example in this paper illustrates that, the described method is simple and effective to achieve the ideal edge of a medical image.","PeriodicalId":208332,"journal":{"name":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117287212","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: 8
A Model of MDVRPTW with Fuzzy Travel Time and Time-Dependent and Its Solution 具有模糊行程时间和时间相关的MDVRPTW模型及其解
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Pub Date : 2008-10-18 DOI: 10.1109/FSKD.2008.77
Lianxi Hong, Min Xu
{"title":"A Model of MDVRPTW with Fuzzy Travel Time and Time-Dependent and Its Solution","authors":"Lianxi Hong, Min Xu","doi":"10.1109/FSKD.2008.77","DOIUrl":"https://doi.org/10.1109/FSKD.2008.77","url":null,"abstract":"The Multi-Depot Vehicle Routing Problem with time-dependent and fuzzy travel time is very difficult to solve to optimality even for relatively small size instances. So few or no literatures have focused on the problem so far. But it is very close to real world and can make the schedule more availability and more flexible. So this paper focuses on modeling and solution of the problem. A model of MDVRPTW with time-dependent and fuzzy travel time is established. Many factors, which include time-dependent problem, fuzzy travel time problem and FIFO problem, are taken into account. Then a hybrid genetic algorithm, which is seasoned with the model and combined with ant colony algorithm, is presented. The computational results show that the approach has good computation performance and acceptable computational time.","PeriodicalId":208332,"journal":{"name":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121357956","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: 2
Information Extraction Based on the Dependency Relationship of Sentences 基于句子依存关系的信息抽取
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Pub Date : 2008-10-18 DOI: 10.1109/FSKD.2008.190
Chuanhua Zeng, Ai Jin, Qingsong Li
{"title":"Information Extraction Based on the Dependency Relationship of Sentences","authors":"Chuanhua Zeng, Ai Jin, Qingsong Li","doi":"10.1109/FSKD.2008.190","DOIUrl":"https://doi.org/10.1109/FSKD.2008.190","url":null,"abstract":"In order to get the information about the technical examination of vehicles in accident from the document, and to provide the foundation for the auto-generation of examination report in natural language, the information extraction techniques are studied, and an information extraction technique based on the dependency relationship of sentences is produced. It constructs the template according to the dependency relationship between the extracted words and frequently-used words. The template, as a set of dependency characteristics in the form of logic expression, is simple and direct. Based on these templates, we can select the word tallying mostly with the dependency characteristics of the template as the final extracted word, so the whole process is straight and speedy.","PeriodicalId":208332,"journal":{"name":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127125446","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
An Improved PIC Algorithm of Background Reconstruction for Detecting Moving Object 一种用于运动目标检测的改进PIC背景重建算法
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Pub Date : 2008-10-18 DOI: 10.1109/FSKD.2008.157
Dou Zhao, Ding Liu, Yanxi Yang
{"title":"An Improved PIC Algorithm of Background Reconstruction for Detecting Moving Object","authors":"Dou Zhao, Ding Liu, Yanxi Yang","doi":"10.1109/FSKD.2008.157","DOIUrl":"https://doi.org/10.1109/FSKD.2008.157","url":null,"abstract":"In machine vision, moving object detection and segment pay more attention to the real-time and the accuracy. Generally, familiar case is immovable camera with the fixed focus in moving object detection, however, it is difficult to detect whole and actual object because of the influence of the environment noise and others. This paper makes some improvement in PIC algorithm and presents a new method of detecting moving object. According to normalization the pixels of the chosen images series used to reconstruct the background, quantization statistic, extent the quantized range, reconstruction the background image, the improved PIC algorithm avoids to providing thresholds of the PIC algorithm manually and removes these steps of combining the approximate gray scope, which needs plenty of time and is hard to realize through programming. After acquiring the reconstructed image, the coarse-fine two steps method is suggested to confirm the object position exactly and complete the moving object detection finally. The experiment results show that the method proposed in this paper needs shorter running time of the program and provides more accurate position of the moving object.","PeriodicalId":208332,"journal":{"name":"2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127196059","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
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