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2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY)最新文献

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An approach to group decision making based on interval-valued intuitionistic fuzzy geometric distance measures 基于区间值直觉模糊几何距离测度的群体决策方法
2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY) Pub Date : 2015-11-01 DOI: 10.1109/IFUZZY.2015.7391901
B. Peng
{"title":"An approach to group decision making based on interval-valued intuitionistic fuzzy geometric distance measures","authors":"B. Peng","doi":"10.1109/IFUZZY.2015.7391901","DOIUrl":"https://doi.org/10.1109/IFUZZY.2015.7391901","url":null,"abstract":"The interval-valued intuitionistic fuzzy set (IVIFS) theory, originated by Atanassov and Gargov [3], has been used in different types of applications such as decision making, pattern recognition and so on. However, so far there has been little investigation of the distance measures of IVIFSs and their applications. In this paper, at first, we develop some new geometric distance measures with interval-valued intuitionistic fuzzy information, including the interval-valued intuitionistic fuzzy weighted geometric distance (IVIFWGD) measure, the interval-valued intuitionistic fuzzy ordered weighted geometric distance (IVIFOWGD) measure and the interval-valued intuitionistic fuzzy hybrid weighted geometric distance (IVIFHWGD) measure. Also, several desirable properties of these new distance measures are studied and a numerical example is given to show application of the distance measure to pattern recognition problems. And then, based on the developed distance measures a consensus reaching process with interval-valued intuitionistic fuzzy preference information for group decision making is proposed. Finally, we apply the developed approach by an illustrative example to group decision making with interval-valued intuitionistic fuzzy information.","PeriodicalId":122167,"journal":{"name":"2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127500344","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
Moment fuzzy control methods for selecting the shortest path 选取最短路径的矩模糊控制方法
2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY) Pub Date : 2015-11-01 DOI: 10.1109/IFUZZY.2015.7391907
T. Tao
{"title":"Moment fuzzy control methods for selecting the shortest path","authors":"T. Tao","doi":"10.1109/IFUZZY.2015.7391907","DOIUrl":"https://doi.org/10.1109/IFUZZY.2015.7391907","url":null,"abstract":"This paper presents moment fuzzy control methods to select the shortest path in a car-like mobile robot model. When the wheel's direction is same with the forward direction that is the direction from car's front center to the destination, the shortest path's rule is gotten. The purpose of moment fuzzy control methods is to select an optimal wheel's angle such that the shortest path's rule will be satisfied. A moment fuzzy theorem is also proposed to ensure that the wheel's direction will approach the shortest path's direction in a stable way. Finally, different destinations are assigned for the robot car to reach along the shortest path in our simulations. These simulations illustrate the excellent performance of the moment fuzzy methods for a car-like mobile robot model to take the shortest path to approach the destination.","PeriodicalId":122167,"journal":{"name":"2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126547632","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
Integrating of business intelligence and CRM in banks: An empirical study of SOM applied in personal customer loans in Taiwan 商业智能与银行客户关系管理的整合:SOM在台湾个人客户贷款中的应用实证研究
2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY) Pub Date : 2015-11-01 DOI: 10.1109/IFUZZY.2015.7391896
Qiao-ling Chen, Jian-Bang Lin
{"title":"Integrating of business intelligence and CRM in banks: An empirical study of SOM applied in personal customer loans in Taiwan","authors":"Qiao-ling Chen, Jian-Bang Lin","doi":"10.1109/IFUZZY.2015.7391896","DOIUrl":"https://doi.org/10.1109/IFUZZY.2015.7391896","url":null,"abstract":"According to the development of economy, the requirements of personal consumer loans have increased. However, the banks are often worried about the status of repayment because the behaviors of every borrower are always fuzzy and uncertain. The most important thing is banks must realize the credit risk of borrowers when they review the applications of personal consumer loans. As a result, this study aims to mine the patterns of default in big data of the banks. The method of self-organizing mapping (SOM) was applied to divide the borrowers into different groups. The result showed we found 5 groups of borrowers and the 5 degrees of default. Finally, this study analyzed the characteristics of borrowers in each groups, and provides the appropriate strategy to individual groups to lower the credit risk in personal consumer loans.","PeriodicalId":122167,"journal":{"name":"2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130204292","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: 5
Intelligent electricity bill saving system for smart home 智能家居智能电费节约系统
2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY) Pub Date : 2015-11-01 DOI: 10.1109/IFUZZY.2015.7391902
Pohsiang Tsai, Bojun Pan
{"title":"Intelligent electricity bill saving system for smart home","authors":"Pohsiang Tsai, Bojun Pan","doi":"10.1109/IFUZZY.2015.7391902","DOIUrl":"https://doi.org/10.1109/IFUZZY.2015.7391902","url":null,"abstract":"One reason that causes world crisis upon our living environments is the effects of global warming caused by substantive carbon dioxide emissions produced by electrical diffuses of power plants industries and family energy uses of electricity consumers. Consequently, for the purpose of reducing this hazardous aftermath, our aim in this paper was not only to propose an intelligent scheduling system for reducing energy consumption costs for smart home users, but, eventually, also could provide certain contributions for reducing these global warming effects more. We therefore proposed a framework using genetic algorithms for optimized home appliances energy uses scheduling. Our extensive experiments showed that our proposed framework could not just provide the optimized scheduling for home appliances uses, with the pre-configured monthly energy expenditure limits, but also could still retain the living comfort of the residents.","PeriodicalId":122167,"journal":{"name":"2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114430579","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
Fuzzy logic approach to predict vehicle crash severity from acceleration data 基于加速度数据预测车辆碰撞严重程度的模糊逻辑方法
2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY) Pub Date : 2015-11-01 DOI: 10.1109/IFUZZY.2015.7391892
B. Munyazikwiye, H. Karimi, K. Robbersmyr
{"title":"Fuzzy logic approach to predict vehicle crash severity from acceleration data","authors":"B. Munyazikwiye, H. Karimi, K. Robbersmyr","doi":"10.1109/IFUZZY.2015.7391892","DOIUrl":"https://doi.org/10.1109/IFUZZY.2015.7391892","url":null,"abstract":"Vehicle crash is a complex behavior to be investigated as a challenging topic in terms of dynamical modeling. On this aim, fuzzy logic can be utilized to analyze the crash dynamics rapidly and simply. In this paper, the experimental data of the frontal crash is recorded using an accelerometer located at the centre of the gravity of the vehicle. The acceleration signal was the raw data from which the collision intensity expressed by the kinetic energy and the jerk were derived. The fuzzy logic model was then developed from the two inputs namely kinetic energy and jerk. The output variable is the crash severity expressed as the dynamic crash. The result shows that the jerk contributes much to the crash than the kinetic energy of the vehicle.","PeriodicalId":122167,"journal":{"name":"2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114779937","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
Speed control design for a vehicle system using fuzzy logic and PID controller 基于模糊逻辑和PID控制器的车辆速度控制系统设计
2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY) Pub Date : 2015-11-01 DOI: 10.1109/IFUZZY.2015.7391894
Olivier Munyaneza, B. Munyazikwiye, H. Karimi
{"title":"Speed control design for a vehicle system using fuzzy logic and PID controller","authors":"Olivier Munyaneza, B. Munyazikwiye, H. Karimi","doi":"10.1109/IFUZZY.2015.7391894","DOIUrl":"https://doi.org/10.1109/IFUZZY.2015.7391894","url":null,"abstract":"This paper consists of designing fuzzy and PID controllers for controlling the vehicle speed. The dynamic of the system is modeled to provide a transfer function for the plant. Fuzzy and PID controller are designed for linear model. The external disturbances such road grade is considered to stabilizing the system. Both controllers are modeled using MATLAB Simulink software. Finally, a comparative assessment of each simulated result is done based on the response characteristics.","PeriodicalId":122167,"journal":{"name":"2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115865722","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: 13
Optimize real-valued RBM with Bidirectional Autoencoder 用双向自编码器优化实值RBM
2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY) Pub Date : 2015-11-01 DOI: 10.1109/IFUZZY.2015.7391888
Qiying Feng, Long Chen, C. L. P. Chen
{"title":"Optimize real-valued RBM with Bidirectional Autoencoder","authors":"Qiying Feng, Long Chen, C. L. P. Chen","doi":"10.1109/IFUZZY.2015.7391888","DOIUrl":"https://doi.org/10.1109/IFUZZY.2015.7391888","url":null,"abstract":"Deep learning increasingly attracted attention after the fast training method of Restricted Boltzmann Machine(RBM) is proposed[1]. Many researches directly constructed deep architecture with stack RBMs to learn the representation of the data, few studied the optimization method to get good RBM parameters. Here proposes a new optimization method for real-valued RBM by minimizing the reconstructed error. Firstly, build and initialize Bidirectional Autoencoder(Bi-Ae). Secondly, minimize the cost function with Stochastic Gradient Descent (SGD) to get the parameters. Thirdly, convert the Bi-AE into RBM with the most suitable parameters. Experiments are executed on the MNIST dataset. Compared with PSO and likelihood maximum optimization methods, the reconstructed errors of the proposed method is 4.02% smaller than the result from error[1], which is advanced.","PeriodicalId":122167,"journal":{"name":"2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129304600","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
Tracking failures detection and correction for face tracking by detection approach based on fuzzy coding histogram and point representation 基于模糊编码直方图和点表示的人脸跟踪故障检测与校正
2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY) Pub Date : 2015-11-01 DOI: 10.1109/IFUZZY.2015.7391890
S. Wibowo, Hansoo Lee, Eun Kyeong Kim, Taehyun Kwon, Sungshin Kim
{"title":"Tracking failures detection and correction for face tracking by detection approach based on fuzzy coding histogram and point representation","authors":"S. Wibowo, Hansoo Lee, Eun Kyeong Kim, Taehyun Kwon, Sungshin Kim","doi":"10.1109/IFUZZY.2015.7391890","DOIUrl":"https://doi.org/10.1109/IFUZZY.2015.7391890","url":null,"abstract":"A tracking approach was shifted from prediction approach to detection approach. One of the parameters to make tracking by detection successfully is the result from previous frame should be correct. It is caused the result from previous frame will be used as a tracking target for next frame. Because of that reason, tracking failures detection and correction needed. In this paper, a method to detecting and correcting of tracking failures by using fuzzy coding histogram and point representation are proposed. Expressly, a fuzzy coding histogram is used to detecting failures tracking and point representation is used to correcting the tracking result. We compared our method with the original tracking by detection method and tracking using point representation method. The results show that our method performed more stable to reach minimum error.","PeriodicalId":122167,"journal":{"name":"2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126469503","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
Fuzzy data mining and web intelligence 模糊数据挖掘与网络智能
2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY) Pub Date : 2015-11-01 DOI: 10.1109/IFUZZY.2015.7391897
V. Poli
{"title":"Fuzzy data mining and web intelligence","authors":"V. Poli","doi":"10.1109/IFUZZY.2015.7391897","DOIUrl":"https://doi.org/10.1109/IFUZZY.2015.7391897","url":null,"abstract":"The data mining on Web is difficult for online analytic processing (OLAP) with BIG DATA. The data mining is made simple by approximating the databases of BIG DATA for knowledge discovery process particularly MapReducing. The approximate information is fuzzy rather than probability. In this paper, fuzzy Web data mining is discussed for BIG DATA for association rules. The query processing is discussed with SQL and Xquery for fuzzy data mining the fuzzy Algorithms are discussed to design queries in data mining. Some examples are discussed for fuzzy Web data mining.","PeriodicalId":122167,"journal":{"name":"2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132532586","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
Composite learning from model reference adaptive fuzzy control 基于模型参考的复合学习自适应模糊控制
2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY) Pub Date : 2015-11-01 DOI: 10.1109/IFUZZY.2015.7391900
Yongping Pan, M. Er, Lin Pan, Haoyong Yu
{"title":"Composite learning from model reference adaptive fuzzy control","authors":"Yongping Pan, M. Er, Lin Pan, Haoyong Yu","doi":"10.1109/IFUZZY.2015.7391900","DOIUrl":"https://doi.org/10.1109/IFUZZY.2015.7391900","url":null,"abstract":"Function approximation accuracy and computational cost are two major issues in approximation-based adaptive fuzzy control. In this paper, a model reference composite learning fuzzy control (MRCLFC) strategy is proposed for a class of affine nonlinear systems with functional uncertainties. In the MRCLFC, a modified modelling error that utilizes data recorded online is defined as the prediction error, a linear filter is applied to estimate the derivatives of plant states, and both the tracking error and the prediction error are exploited to update parametric estimates. It is proven that the closed-loop system achieves semiglobal practical exponential stability by an interval-excitation condition which is much weaker than a persistent-excitation condition. The proposed strategy can guarantee accurate function approximation under greatly reduced computational cost. The effectiveness of the proposed MRCLFC strategy has been verified by applying it to an control problem of aircraft wing rock.","PeriodicalId":122167,"journal":{"name":"2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132781264","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
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