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International Conference on Fuzzy Systems最新文献

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A fuzzy ontology approach to represent user profiles in e-learning environments 一种表示电子学习环境中用户档案的模糊本体方法
International Conference on Fuzzy Systems Pub Date : 2010-07-18 DOI: 10.1109/FUZZY.2010.5584789
M. Satler, F. P. Romero, Víctor Hugo Menéndez Domínguez, Alfredo Zapata, Manuel E. Prieto
{"title":"A fuzzy ontology approach to represent user profiles in e-learning environments","authors":"M. Satler, F. P. Romero, Víctor Hugo Menéndez Domínguez, Alfredo Zapata, Manuel E. Prieto","doi":"10.1109/FUZZY.2010.5584789","DOIUrl":"https://doi.org/10.1109/FUZZY.2010.5584789","url":null,"abstract":"Ontologies represent a method of sharing and reusing knowledge on the semantic web. A fuzzy ontology is an extension of domain ontologies for solving the problems of uncertainty. This paper shows how a Fuzzy Ontology based approach can represent user profiles in e-learning environments. The ontological representation of the user profile enhances the performance in tasks such as filtering and information retrieval. An algorithm that allows automatically creating the construction of the ontology is also introduced. This approach has been integrated into a management tool for Learning Objects, in which each user profile is built from Learning Objects published by the user himself. The initial experiments confirm that the automatically obtained fuzzy ontology is a good representation of the user's preferences. The experiment results also indicate that the approach is useful and warrants further research.","PeriodicalId":377799,"journal":{"name":"International Conference on Fuzzy Systems","volume":"15 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":"131245348","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: 24
Using a fuzzy agent in modeling lead-acid battery operating in grid connected wind energy conversion systems 利用模糊代理对并网风能转换系统中铅酸蓄电池的运行进行建模
International Conference on Fuzzy Systems Pub Date : 2010-07-18 DOI: 10.1109/FUZZY.2010.5584809
M. Ibrahim, A. Khairy, H. Hagras, M. Zaher
{"title":"Using a fuzzy agent in modeling lead-acid battery operating in grid connected wind energy conversion systems","authors":"M. Ibrahim, A. Khairy, H. Hagras, M. Zaher","doi":"10.1109/FUZZY.2010.5584809","DOIUrl":"https://doi.org/10.1109/FUZZY.2010.5584809","url":null,"abstract":"This paper investigates the performance of a lead-acid battery in a grid connected wind energy generator system. Wind energy has gained much credit in the past two decades as a sustainable energy resource. The penetration of wind energy generators into the electric utility grids is expected to increase to about 1.5 TW within the present decade. Due to the intermittent nature of the wind, there have been serious concerns about reliability and operation of the utility power grids. Battery storage is suggested to compensate wind power fluctuations and smooth the power fed to the utility grids. The battery storage in such applications has dynamic operating conditions and is subjected to different ageing mechanisms which stimulate the capacity degradation and hence influence the feasibility of their implementation. This paper investigates the implementation of fuzzy agent modeling as a powerful technique to estimate the dynamic and sophisticated electrochemical battery degradation mechanisms. Accordingly, the real behavior, the feasibility of the battery and its effect on wind power fed to the utility grid can be judged. The investigated system is simulated using real measurement data of a 600 kW rated power wind turbine. The simulation results of different battery capacities show that the integration of the battery storage has compensated the fluctuations of the generated wind power and smoothed the power fed to the utility grid. Moreover, the fuzzy agent has generated very important information about the battery degradation and available capacity (in this case of about 85%) after one year of operation.","PeriodicalId":377799,"journal":{"name":"International Conference on Fuzzy Systems","volume":"6 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":"131742854","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
The behavior of particles in the Particle Swarm Clustering algorithm 粒子群聚类算法中粒子的行为
International Conference on Fuzzy Systems Pub Date : 2010-07-18 DOI: 10.1109/FUZZY.2010.5584118
Alexandre Szabo, Ana Karina Fontes Prior, L. Castro
{"title":"The behavior of particles in the Particle Swarm Clustering algorithm","authors":"Alexandre Szabo, Ana Karina Fontes Prior, L. Castro","doi":"10.1109/FUZZY.2010.5584118","DOIUrl":"https://doi.org/10.1109/FUZZY.2010.5584118","url":null,"abstract":"The Particle Swarm Clustering (PSC) algorithm uses collective intelligence to solve clustering problems. It simulates the interaction of individuals, which use their own experience (cognitive term), social experience (social term) and interaction with the environment (self-organizing term) to cluster objects in different groups. In this work a study of the behavior of particles and an analysis of the PSC convergence were performed considering each term that composes the particles' adaptation equation. The objective was to evaluate the relevance of each of these terms within the context of clustering data.","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":"125332398","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
Segmentation and outlier removal in 3D line identification based on fuzzy clustering 基于模糊聚类的三维直线识别分割与异常点去除
International Conference on Fuzzy Systems Pub Date : 2010-07-18 DOI: 10.1109/FUZZY.2010.5584309
Ba Thach Nguyen, Sukhan Lee
{"title":"Segmentation and outlier removal in 3D line identification based on fuzzy clustering","authors":"Ba Thach Nguyen, Sukhan Lee","doi":"10.1109/FUZZY.2010.5584309","DOIUrl":"https://doi.org/10.1109/FUZZY.2010.5584309","url":null,"abstract":"In this paper, we present a novel method based on clustering for identifying 3D line from point clouds, called “self-organizing fuzzy k-means algorithm”. The algorithm automatically finds the optimal number of cluster and self organizes the clusters based on inter/intra-cluster distances and cluster's performance evaluation. The self-organizing fuzzy k-means is applied in 3D line identification from point clouds. We use the point clouds provided by Stereo camera and 2D images. The 3D point clouds of each line is clustered by clustering algorithm, then we perform eigen-analysis on clusters and estimate the final 3D lines; the 3D lines can be cut off into several segments. In addition, to increase the accuracy of detection, the error evaluation is invoked to analyze the error of the 3D candidate lines. Our algorithm was evaluated on the real test scenes, which content noisy point clouds, and shows the high performance and robust results.","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":"126424955","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: 3
Economic trends prediction based on linguistic reasoning 基于语言推理的经济趋势预测
International Conference on Fuzzy Systems Pub Date : 2010-07-18 DOI: 10.1109/FUZZY.2010.5584395
S. Ito, T. Takagi
{"title":"Economic trends prediction based on linguistic reasoning","authors":"S. Ito, T. Takagi","doi":"10.1109/FUZZY.2010.5584395","DOIUrl":"https://doi.org/10.1109/FUZZY.2010.5584395","url":null,"abstract":"Conventionally, economic forecasts were often made with numerical methods because of computational restrictions. However, causal events of economic movements are often linguistically described. Furthermore, they strongly affect these movements, e.g., the subprime loans in the case of the Lehman shock. We pay attention to these causal events. Economists remember past economic events that are linguistically expressed and they use them when they predict future movements in newly encountered economic conditions. However an ordinary logical system cannot cope with this problem; match events in different expressions and predict future movements by using words. We propose the use of a prediction system that is based on data written in natural language and examine it using a real corpus from a news article comparing the movement of real stock.","PeriodicalId":377799,"journal":{"name":"International Conference on Fuzzy Systems","volume":"52 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":"126926949","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
MOEA based hierarchical fuzzy control over the set of user-defined initial conditions 基于MOEA的自定义初始条件的层次模糊控制
International Conference on Fuzzy Systems Pub Date : 2010-07-18 DOI: 10.1109/FUZZY.2010.5584703
J. Zajaczkowski, B. Verma
{"title":"MOEA based hierarchical fuzzy control over the set of user-defined initial conditions","authors":"J. Zajaczkowski, B. Verma","doi":"10.1109/FUZZY.2010.5584703","DOIUrl":"https://doi.org/10.1109/FUZZY.2010.5584703","url":null,"abstract":"A compositional method for hierarchical fuzzy control over the user-defined set of initial conditions is presented. The control system is found by using a multi-objective evolutionary algorithm. The inverted pendulum system is selected as an example of a dynamical system and used to test the proposed method. The pre-defined set of initial conditions includes dynamical and static conditions of the system. Control system is designed as a three-layered hierarchical fuzzy logic structure. The test results showed that the proposed method has a relatively high success rate in terms of the number of initial conditions from which the system is controlled to TR. The best achieved result was 94.5% success rate. The proposed compositional method can be applied to a wide range of dynamical systems.","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":"121107447","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
A quantitative comparison of interval type-2 and type-1 fuzzy logic systems: First results 区间2型和1型模糊逻辑系统的定量比较:初步结果
International Conference on Fuzzy Systems Pub Date : 2010-07-18 DOI: 10.1109/FUZZY.2010.5584727
J. Mendel
{"title":"A quantitative comparison of interval type-2 and type-1 fuzzy logic systems: First results","authors":"J. Mendel","doi":"10.1109/FUZZY.2010.5584727","DOIUrl":"https://doi.org/10.1109/FUZZY.2010.5584727","url":null,"abstract":"The question “When will an IT2 FLS outperform a T1 FLS?” has been asked by many, and is acknowledged by many experts to be arguably the most important unanswered question in the T2 field. As a research problem, this question turns into: Establish when and by how much a type-2 fuzzy logic system (T2 FLS) will outperform a type-1 (T1) FLS. This paper provides first results on solving this problem. Its approach is novel because it does not focus immediately on a specific application, but instead focuses on the common component to all performance analyses, thereby providing results that can be used by others in their application-based performance comparisons. The Wu-Mendel minimax uncertainty bounds [16], which in the past have been used to approximate the type-reduced set, and to also act as a starting point for designs of IT2 FLSs, play the key role in this paper. Although comparing an IT2 FLS to a T1 FLS seems like a daunting task, because of the complicated nature of the equations that describe them, this paper shows that when an IT2 FLS is expanded about a T1 FLS-itself a new concept-, surprisingly, very simple first results are obtained.","PeriodicalId":377799,"journal":{"name":"International Conference on Fuzzy Systems","volume":"62 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":"116689890","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: 43
A category-based information filtering approach based on interval type 2 fuzzy sets 一种基于区间2型模糊集的分类信息过滤方法
International Conference on Fuzzy Systems Pub Date : 2010-07-18 DOI: 10.1109/FUZZY.2010.5584813
F. P. Romero, J. Serrano-Guerrero, J. A. Olivas, Andrés Soto
{"title":"A category-based information filtering approach based on interval type 2 fuzzy sets","authors":"F. P. Romero, J. Serrano-Guerrero, J. A. Olivas, Andrés Soto","doi":"10.1109/FUZZY.2010.5584813","DOIUrl":"https://doi.org/10.1109/FUZZY.2010.5584813","url":null,"abstract":"Category-based information filtering is ground on the representation of user preferences according to a set of categories of similar items. The use of type 1 fuzzy sets provides a good method to represent categories when only one static interpretation of them is considered. This representation is not enough when documents do not have the same meaning for two different users because there are some degrees of subjectivity. On the other hand, type 2 fuzzy sets have been successfully applied to manage uncertainty more effectively than type-1 fuzzy sets in several environments. This paper presents a method to manage efficiently uncertainties in the filtering process in environments where there is a constant flow of new information (news, e-mail, etc.) and multiple users are involved. The proposed solution is based on the extension of the categories-based filtering method using interval type 2 fuzzy sets for representing each category and the user preferences. Experimental results, that illustrate the feasibility of this approach, are provided.","PeriodicalId":377799,"journal":{"name":"International Conference on Fuzzy Systems","volume":"37 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":"121823402","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
Support Vector-trained Recurrent Fuzzy System 支持向量训练的递归模糊系统
International Conference on Fuzzy Systems Pub Date : 2010-07-18 DOI: 10.1109/FUZZY.2010.5584494
I. Chung, Chia-Feng Juang, Cheng-Da Hsieh
{"title":"Support Vector-trained Recurrent Fuzzy System","authors":"I. Chung, Chia-Feng Juang, Cheng-Da Hsieh","doi":"10.1109/FUZZY.2010.5584494","DOIUrl":"https://doi.org/10.1109/FUZZY.2010.5584494","url":null,"abstract":"This paper proposes a Support Vector-trained Recurrent Fuzzy System (SV-RFS) which comprises recurrent Takagi-Sugeno (TS) fuzzy if-then rules. The SV-RFS memories past input information by feeding the past firing strength of a fuzzy rule back to itself. The rules are generated based on a clustering-like algorithm. The feedback loop gains and consequent part parameters are learned through support vector regression (SVR) in order to improve system generalization ability. The SV-RFS is applied to noisy chaotic sequence prediction to verify its effectiveness.","PeriodicalId":377799,"journal":{"name":"International Conference on Fuzzy Systems","volume":"34 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":"124965861","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
Meta-learning for time series forecasting in the NN GC1 competition 神经网络GC1竞赛中用于时间序列预测的元学习
International Conference on Fuzzy Systems Pub Date : 2010-07-18 DOI: 10.1109/FUZZY.2010.5584001
Christiane Lemke, B. Gabrys
{"title":"Meta-learning for time series forecasting in the NN GC1 competition","authors":"Christiane Lemke, B. Gabrys","doi":"10.1109/FUZZY.2010.5584001","DOIUrl":"https://doi.org/10.1109/FUZZY.2010.5584001","url":null,"abstract":"There are no algorithms that generally perform better or worse than random when looking at all possible data sets according to the no-free-lunch theorem. A specific forecasting method will hence naturally have different performances in different empirical studies. This makes it impossible to draw general conclusions, however, there will of course be specific problems for which one algorithm performs better than another in practice. Meta-learning exploits this fact by linking characteristics of the data set to the performances of methods, adapting the selection or combination of base methods to a specific problem. This contribution describes an approach using meta-learning for time series forecasting in the NN GC1 competition. In order to generate bigger and more reliable meta-data set, data of the past NN3 and NN5 competitions have been included. A pool of individual forecasting and combination models are combined using a ranking algorithm with weights being determined by past performance on similar series.","PeriodicalId":377799,"journal":{"name":"International Conference on Fuzzy Systems","volume":"19 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":"125239785","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: 22
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