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International Conference on Fuzzy Systems最新文献

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Examining the continuity of type-1 and interval type-2 fuzzy logic systems 检验1型和区间2型模糊逻辑系统的连续性
International Conference on Fuzzy Systems Pub Date : 2010-07-18 DOI: 10.1109/FUZZY.2010.5584482
Dongrui Wu, J. Mendel
{"title":"Examining the continuity of type-1 and interval type-2 fuzzy logic systems","authors":"Dongrui Wu, J. Mendel","doi":"10.1109/FUZZY.2010.5584482","DOIUrl":"https://doi.org/10.1109/FUZZY.2010.5584482","url":null,"abstract":"This paper studies the continuity of the input-output mappings of fuzzy logic systems (FLSs), including both type-1 (T1) and interval type-2 (IT2) FLSs. We show that a T1 FLS being an universal approximator is equivalent to saying that a T1 FLS has a continuous input-output mapping. We also derive the condition under which a T1 FLS is discontinuous. For IT2 FLSs using Karnik-Mendel type-reduction and center-of-sets defuzzification, we derive the conditions under which continuous and discontinuous input-output mappings can be obtained. Our results will be very useful in selecting the parameters of the membership functions to achieve a desired continuity (e.g., for most traditional modeling and control applications) or discontinuity (e.g., for hybrid and switched systems modeling and control).","PeriodicalId":377799,"journal":{"name":"International Conference on Fuzzy Systems","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130706102","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: 7
Ontology matching for the semantic annotation of images 图像语义标注的本体匹配
International Conference on Fuzzy Systems Pub Date : 2010-07-18 DOI: 10.1109/FUZZY.2010.5584354
Nicolas James, Konstantin Todorov, C. Hudelot
{"title":"Ontology matching for the semantic annotation of images","authors":"Nicolas James, Konstantin Todorov, C. Hudelot","doi":"10.1109/FUZZY.2010.5584354","DOIUrl":"https://doi.org/10.1109/FUZZY.2010.5584354","url":null,"abstract":"The linguistic description, i.e. semantic annotation of images can benefit from representations of useful concepts and the links between them as ontologies. Recently, several multimedia ontologies have been proposed in the literature as suitable knowledge models to bridge the well known semantic gap between low level features of image content and its high level conceptual meaning. Nevertheless, these multimedia ontologies are often dedicated to (or initially built for) particular needs or a particular application. Ontology matching, defined as the process of relating different heterogeneous models, could be a suitable approach to solve several interoperability issues that coexist in semantic image annotation and retrieval. In this paper, we propose an original and generic instance-based ontology matching approach and a methodology to extract a minimal ontology defined as the common reference between different heterogeneous ontologies. Then, this approach is applied to two different semantic image retrieval issues: the bridging of the semantic gap by the matching of a multimedia ontology with a common-sense knowledge ontology and the matching of different multimedia ontologies to extract a common reference knowledge model dedicated to several multimedia applications.","PeriodicalId":377799,"journal":{"name":"International Conference on Fuzzy Systems","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131170287","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: 20
Scalable fuzzy neighborhood DBSCAN 可伸缩模糊邻域DBSCAN
International Conference on Fuzzy Systems Pub Date : 2010-07-18 DOI: 10.1109/FUZZY.2010.5584527
J. K. Parker, L. Hall, A. Kandel
{"title":"Scalable fuzzy neighborhood DBSCAN","authors":"J. K. Parker, L. Hall, A. Kandel","doi":"10.1109/FUZZY.2010.5584527","DOIUrl":"https://doi.org/10.1109/FUZZY.2010.5584527","url":null,"abstract":"The majority of data available in most disciplines is unlabeled and unclassified. The amount of data is often massive, hence scalable processing methods are required. One method of providing structure to unlabeled data is to group it by clustering. Density based methods discover the number of clusters. Additionally, the shape of such clusters can also be irregular. In this paper we examine a version of DBSCAN modified to use fuzzy membership functions (FN-DBSCAN). FN-DBSCAN was implemented using the WEKA data mining framework and a scalable technique (SFN-DBSCAN) is simulated using the framework. Experimental results show that SFN-DBSCAN can be over three times as fast as FN-DBSCAN for small to medium size data. The resulting cluster assignments match at an average rate of 90% when compared with assignments by FN-DBSCAN. SFN-DBSCAN's speed increases proportionally with respect to the number of subsets, but cluster assignment concurrence between FN-DBSCAN and SFN-DBSCAN suffers from degradation as the number of subsets increase.","PeriodicalId":377799,"journal":{"name":"International Conference on Fuzzy Systems","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131900004","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
Exploiting Timed Automata-based Fuzzy Controllers and data mining to detect computer network intrusions 利用时间自动机模糊控制器和数据挖掘技术检测计算机网络入侵
International Conference on Fuzzy Systems Pub Date : 2010-07-18 DOI: 10.1109/FUZZY.2010.5584893
G. Acampora
{"title":"Exploiting Timed Automata-based Fuzzy Controllers and data mining to detect computer network intrusions","authors":"G. Acampora","doi":"10.1109/FUZZY.2010.5584893","DOIUrl":"https://doi.org/10.1109/FUZZY.2010.5584893","url":null,"abstract":"A Network Intrusion Detection System is a network monitoring framework that tries to detect malicious network activity such as port scans, denial of service or other attempts to crack computer network environments. The main aim of intrusion detection is to identify unauthorized use, misuse, and abuse of computers by external penetrators. In real life, however, temporal changes in network intrusion patterns and characteristics tend to invalidate the usability of existing intrusion detection systems. In order to solve this drawback, our paper introduces a novel kind of fuzzy controller, known as Timed Automata-based Fuzzy Controllers, and it presents a data mining approach able to learn the most suitable controller that manages, in efficient way, the computer network dynamism and support networks' administrators to prevent eventual damages coming from unauthorized network intrusion.","PeriodicalId":377799,"journal":{"name":"International Conference on Fuzzy Systems","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133804532","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: 7
Linguistic description of traffic in a roundabout 环岛交通的语言描述
International Conference on Fuzzy Systems Pub Date : 2010-07-18 DOI: 10.1109/FUZZY.2010.5584060
G. Triviño, Alejandro Sanchez, A. S. Montemayor, J. Pantrigo, R. Cabido, Eduardo G. Pardo
{"title":"Linguistic description of traffic in a roundabout","authors":"G. Triviño, Alejandro Sanchez, A. S. Montemayor, J. Pantrigo, R. Cabido, Eduardo G. Pardo","doi":"10.1109/FUZZY.2010.5584060","DOIUrl":"https://doi.org/10.1109/FUZZY.2010.5584060","url":null,"abstract":"The linguistic description of a physical phenomenon is a summary of the available information where certain relevant aspects are remarked while other irrelevant aspects remain hidden. This paper deals with the development of computational systems capable to generate linguistic descriptions from images captured by a video camera. The problem of linguistically labeling images in a database is a challenge where still much work remains to be done. In this paper, we contribute to this field using a model of the observed phenomenon that allows us to interpret the content of images. We build the model by combining techniques from Computer Vision with ideas from the Zadeh's Computational Theory of Perceptions. We include a practical application consisting of a computational system capable to provide a linguistic description of the behavior of traffic in a roundabout.","PeriodicalId":377799,"journal":{"name":"International Conference on Fuzzy Systems","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133855586","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: 30
Continuous fuzzy sets as probabilities of continuous fuzzy events 连续模糊集作为连续模糊事件的概率
International Conference on Fuzzy Systems Pub Date : 2010-07-18 DOI: 10.1109/FUZZY.2010.5584432
E. Rakus-Andersson
{"title":"Continuous fuzzy sets as probabilities of continuous fuzzy events","authors":"E. Rakus-Andersson","doi":"10.1109/FUZZY.2010.5584432","DOIUrl":"https://doi.org/10.1109/FUZZY.2010.5584432","url":null,"abstract":"In the first part of this study we explore continuous fuzzy numbers in the interval- and the α-cut forms to detect their similar nature. The conversion from one form to the other is a question of using the appropriate apparatus, which we also provide. Since the fuzzy numbers can reproduce fuzzy events we then will make a trial of extending the concept of fuzzy probability, defined by R. Yager [1] for discrete fuzzy events, on continuous fuzzy events. In order to fulfill the task we utilize conclusions made about fuzzy numbers to propose an initial conception of approximating the Gauss curve by a particularly designed function originated from the π-class functions. Due to the procedure of the approximation, characterized by an irrelevant cumulative error, we expand fuzzy probabilities of continuous fuzzy events in the form of continuous fuzzy sets. Furthermore, we assume that this sort of probability holds some conditions formulated for probabilities of discrete fuzzy events [2]-[7].","PeriodicalId":377799,"journal":{"name":"International Conference on Fuzzy Systems","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115842984","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
Recurrent fuzzy neural computation: Modeling, learning and application 递归模糊神经计算:建模、学习与应用
International Conference on Fuzzy Systems Pub Date : 2010-07-18 DOI: 10.1109/FUZZY.2010.5584099
R. Ballini, F. Gomide
{"title":"Recurrent fuzzy neural computation: Modeling, learning and application","authors":"R. Ballini, F. Gomide","doi":"10.1109/FUZZY.2010.5584099","DOIUrl":"https://doi.org/10.1109/FUZZY.2010.5584099","url":null,"abstract":"A novel recurrent neurofuzzy network is developed in this paper. The network model is composed by two strucutres: a fuzzy system and a neural network. The fuzzy system contains fuzzy neurons modeled using t-norms and s-norms. The neural network is composed by nonlinear elements placed in series with the fuzzy system. The network model implicitly encodes a fuzzy rule-based system and its recurrent multilayered structure performs fuzzy inference. The topology induces a clear relationship between the network structure and the associated fuzzy rule-based system. Network learning involves three main steps. The first step uses a modified vector quantization approach to granulate the input universes. The next step assembles the network connections and their initial, randomly chosen weights. The third step uses two main paradigms to update the network weights: gradient descent and gradient projection method. The recurrent fuzzy neural network is particularly suitable to model nonlinear dynamic systems and to learn sequences. Computational experiment with a classic prediction problem benchmark shows that the fuzzy neural model outperforms a finite impulse response neural network.","PeriodicalId":377799,"journal":{"name":"International Conference on Fuzzy Systems","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124253016","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 two-phase fuzzy mining approach 两阶段模糊挖掘方法
International Conference on Fuzzy Systems Pub Date : 2010-07-18 DOI: 10.1109/FUZZY.2010.5584373
Chun-Wei Lin, T. Hong, Wen-Hsiang Lu
{"title":"A two-phase fuzzy mining approach","authors":"Chun-Wei Lin, T. Hong, Wen-Hsiang Lu","doi":"10.1109/FUZZY.2010.5584373","DOIUrl":"https://doi.org/10.1109/FUZZY.2010.5584373","url":null,"abstract":"In this paper, we propose a two-phase fuzzy mining approach based on a tree structure to discover fuzzy frequent itemsets from a quantitative database. A simple tree structure called the upper-bound fuzzy frequent-pattern tree (abbreviated as UBFFP tree) is designed to help achieve the purpose. The two-phase fuzzy mining approach can easily derive the upper-bound fuzzy supports of itemsets through the tree and prune unpromising itemsets in the first phase, and then finds the actual frequent fuzzy itemsets in the second phase. Experimental results also show the good performance of the proposed approach.","PeriodicalId":377799,"journal":{"name":"International Conference on Fuzzy Systems","volume":"323 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124570691","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
Uncertainty modeling in dynamic clustering — A soft computing perspective 动态聚类中的不确定性建模——软计算视角
International Conference on Fuzzy Systems Pub Date : 2010-07-18 DOI: 10.1109/FUZZY.2010.5584840
Georg Peters, R. Weber, Fernando A. Crespo
{"title":"Uncertainty modeling in dynamic clustering — A soft computing perspective","authors":"Georg Peters, R. Weber, Fernando A. Crespo","doi":"10.1109/FUZZY.2010.5584840","DOIUrl":"https://doi.org/10.1109/FUZZY.2010.5584840","url":null,"abstract":"Uncertainty plays an important role in clustering. For example in customer segmentation we may be faced with the situation that a certain customer not necessarily belongs to just one segment, i.e. his/her class assignment is uncertain. Several cluster algorithms have been proposed that employ uncertainty modeling in different ways. The most frequently used techniques are probability theory, fuzzy logic, and recently rough sets. If uncertainty modeling is already important in static clustering this becomes even more important in dynamic clustering where several elements of the respective cluster can change over time. Changes produce uncertainty and that is where uncertainty modeling in dynamic clustering comes into play. In this paper we present briefly two cluster algorithms that employ soft computing approaches and provide a comparison regarding their capabilities to capture uncertainties in dynamic environments. Future research issues for this area are also identified.","PeriodicalId":377799,"journal":{"name":"International Conference on Fuzzy Systems","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114335810","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: 7
Fuzzy generalized aggregation operators in a unified model between the probability, the weighted average and the OWA operator 模糊广义聚合算子在概率、加权平均和OWA算子之间建立了统一的模型
International Conference on Fuzzy Systems Pub Date : 2010-07-18 DOI: 10.1109/FUZZY.2010.5584795
J. Merigó
{"title":"Fuzzy generalized aggregation operators in a unified model between the probability, the weighted average and the OWA operator","authors":"J. Merigó","doi":"10.1109/FUZZY.2010.5584795","DOIUrl":"https://doi.org/10.1109/FUZZY.2010.5584795","url":null,"abstract":"We introduce a new model that unifies the probability, the weighted average and the ordered weighted average considering the degree of importance that each concept has in the aggregation. Moreover, this approach generalizes a wide range of aggregation operators by using generalized means. Furthermore, this approach is able to assess uncertain information that can be assessed with fuzzy numbers. We call it the fuzzy generalized probabilistic ordered weighted averaging weighted average (FGPOWAWA) operator. Its main advantage is that it includes a wide range of aggregation operators such as the FPOWAWA, the quadratic FPOWAWA, the arithmetic FOWAWA, the arithmetic FPOWA, the FPWA and the double FOWA operator. We further generalize this approach by using quasi-arithmetic means obtaining the Quasi-FPOWAWA operator. We also analyze the applicability of this new approach in decision making.","PeriodicalId":377799,"journal":{"name":"International Conference on Fuzzy Systems","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114873750","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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