2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)最新文献_第4页

Non-commutativity and many-valuedness: The topological representation of the spectrum of C∗-algebras 非交换性与多值性:C * -代数谱的拓扑表示

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2017-07-09 DOI: 10.1109/FUZZ-IEEE.2017.8015377

P. Eklund, Javier Gutiérrez García, U. Höhle, J. Kortelainen

引用次数: 0

Reliability-guided fuzzy classifier ensemble 可靠性导向模糊分类器集成

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2017-07-09 DOI: 10.1109/FUZZ-IEEE.2017.8015407

Tianhua Chen, P. Su, C. Shang, Q. Shen

{"title":"Reliability-guided fuzzy classifier ensemble","authors":"Tianhua Chen, P. Su, C. Shang, Q. Shen","doi":"10.1109/FUZZ-IEEE.2017.8015407","DOIUrl":"https://doi.org/10.1109/FUZZ-IEEE.2017.8015407","url":null,"abstract":"Classifier ensembles form an important approach to improving classification performance. As such, there have been different proposals made in the literature that provide a range of means to construct and aggregate classifier ensembles. However, the resulting systems may contain unreliable members with false or biased judgements in the ensemble. The removal of unreliable members is necessary to optimise the overall performance of such systems. Smaller ensembles involving reduced ensemble members also helps relax the requirement of computational memory, thereby strengthening the system's run-time efficiency. To differentiate the potential contributions of different ensemble members while reducing the adverse impact of any unreliable judgement upon the system, a nearest neighbour-based reliability measure is incorporated into the process of classifier ensemble selection. In particular, reliabilities of selected ensemble members are perceived as a stress function, from which argument-dependent weights are heuristically generated for final aggregated decision. Experimental investigations are carried out, demonstrating the efficacy of the proposed approach, where fuzzy classifiers are utilised as base members of the emerging ensemble.","PeriodicalId":408343,"journal":{"name":"2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115567648","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

Investigating live streaming data for student behaviour modelling 为学生行为建模调查直播数据

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2017-07-09 DOI: 10.1109/FUZZ-IEEE.2017.8015451

Jie Yang, Jun Ma, S. Howard

{"title":"Investigating live streaming data for student behaviour modelling","authors":"Jie Yang, Jun Ma, S. Howard","doi":"10.1109/FUZZ-IEEE.2017.8015451","DOIUrl":"https://doi.org/10.1109/FUZZ-IEEE.2017.8015451","url":null,"abstract":"Modelling technology integration in the teaching and learning environment is a complex, uncertain and dynamic practice. A large amount of student behaviour data has been gathered literately for different processing purposes. Yet, considerable questions are still remaining due to the huge data volume, diversification and uncertainty. In this work, we implement a big-data analytical framework for online behaviour modelling, particularly taking streaming data of students' online activity from their laptop usage as an illustrative example. The proposed framework covers details from accessing streaming records to storing heterogeneous data. Furthermore, the work also demonstrates the use of a TF-IDF based feature generation and fuzzy representation strategy to discover critical patterns via this behaviour data. The accuracy of the modelling work is evaluated using students' score on a national-wide test. Experimental results show that the employed TF-IDF feature is much stabler than other traditional features, thereby achieving a better modelling performance. In summary, the simulation result demonstrates the flexibility and applicability of the proposed framework for processing complex behaviour data, and revealing important patterns for decision making.","PeriodicalId":408343,"journal":{"name":"2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"272 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115599342","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

Multi-source sensor fusion for small unmanned aircraft systems using fuzzy logic 基于模糊逻辑的小型无人机多源传感器融合

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2017-07-09 DOI: 10.1109/FUZZ-IEEE.2017.8015593

Brandon Cook, Kelly Cohen

引用次数: 4

Dynamic QoS solution for enterprise networks using TSK fuzzy interpolation 基于TSK模糊插值的企业网络动态QoS解决方案

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2017-07-09 DOI: 10.1109/FUZZ-IEEE.2017.8015711

Jie Li, Longzhi Yang, Xin Fu, F. Chao, Yanpeng Qu

{"title":"Dynamic QoS solution for enterprise networks using TSK fuzzy interpolation","authors":"Jie Li, Longzhi Yang, Xin Fu, F. Chao, Yanpeng Qu","doi":"10.1109/FUZZ-IEEE.2017.8015711","DOIUrl":"https://doi.org/10.1109/FUZZ-IEEE.2017.8015711","url":null,"abstract":"The Quality of Services (QoS) is the measure of data transmission quality and service availability of a network, aiming to maintain the data, especially delay-sensitive data such as VoIP, to be transmitted over the network with the required quality. Major network device manufacturers have each developed their own smart dynamic QoS solutions, such as AutoQoS supported by Cisco, CoS (Class of Service) by Netgear devices, and QoS Maps on SROS (Secure Router Operating System) provided by HP, to maintain the service level of network traffic. Such smart QoS solutions usually only work for manufacture qualified devices and otherwise only a pre-defined static policy mapping can be applied. This paper presents a dynamic QoS solution based on the differentiated services (DiffServ) approach for enterprise networks, which is able to modify the priority level of a packet in real time by adjusting the value of Differentiated Services Code Point (DSCP) in Internet Protocol (IP) header of network packets. This is implemented by a 0-order TSK fuzzy model with a sparse rule base which is developed by considering the current network delay, application desired priority level and user current priority group. DSCP values are dynamically generated by the TSK fuzzy model and updated in real time. The proposed system has been evaluated in a real network environment with promising results generated.","PeriodicalId":408343,"journal":{"name":"2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125670116","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

rLDCP: R package for text generation from data rLDCP:用于从数据生成文本的R包

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2017-07-09 DOI: 10.1109/FUZZ-IEEE.2017.8015487

Patricia Conde-Clemente, J. M. Alonso, G. Triviño

引用次数: 9

A type-2 fuzzy logic system for event detection in soccer videos 足球视频事件检测的2型模糊逻辑系统

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2017-07-09 DOI: 10.1109/FUZZ-IEEE.2017.8015426

Wei Song, H. Hagras

引用次数: 10

Looking for a real-world-semantics-based approach to the interpretability of fuzzy systems 寻找一种基于现实世界语义的模糊系统可解释性方法

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2017-07-09 DOI: 10.1109/FUZZ-IEEE.2017.8015562

Cat Ho, J. M. Alonso

引用次数: 7

Interval type-2 fuzzy demand based vendor managed inventory model 基于区间型2模糊需求的供应商管理库存模型

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2017-07-09 DOI: 10.1109/FUZZ-IEEE.2017.8015738

Zubair Ashraf, Deepika Malhotra, Pranab K. Muhuri, Q. Lohani

{"title":"Interval type-2 fuzzy demand based vendor managed inventory model","authors":"Zubair Ashraf, Deepika Malhotra, Pranab K. Muhuri, Q. Lohani","doi":"10.1109/FUZZ-IEEE.2017.8015738","DOIUrl":"https://doi.org/10.1109/FUZZ-IEEE.2017.8015738","url":null,"abstract":"Vendor managed inventory (VMI) is one of the well-known strategies of merchandizing between suppliers and retailers. The essential aspect in VMI model is to fulfill the demand of the retailers by the suppliers. Since, the costs of items are highly volatile, it is not possible to design a VMI model with deterministic demand. In this paper, we have considered one supplier and retailer to perform business of multi-product under VMI model with uncertain demand. Thus, it proposes a novel VMI model, termed as ‘interval type-2 fuzzy vendor managed inventory (IT2 FVMI) model’ that considers interval type-2 fuzzy number to represent the uncertain demand. The objective is to minimize the total cost of VMI by finding the optimum ordered quantity and backordered level. We develop a particle swarm optimization algorithm based solution approach to solve it. A suitable real-world application is considered to perform the simulation. We have considered different number of instances of the products to obtain the results. By comparing the results with the deterministic demand and type-1 fuzzy number, we show the efficacy of our proposed IT2 FVMI model.","PeriodicalId":408343,"journal":{"name":"2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123954013","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

Type reduction techniques for two-dimensional interval type-2 fuzzy sets 二维区间型-2模糊集的类型约简技术

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2017-07-09 DOI: 10.1109/FUZZ-IEEE.2017.8015724

Vaibhav Saxena, Nikhil Yadala, R. Chourasia, F. Rhee

{"title":"Type reduction techniques for two-dimensional interval type-2 fuzzy sets","authors":"Vaibhav Saxena, Nikhil Yadala, R. Chourasia, F. Rhee","doi":"10.1109/FUZZ-IEEE.2017.8015724","DOIUrl":"https://doi.org/10.1109/FUZZ-IEEE.2017.8015724","url":null,"abstract":"In this paper, we address the issue of type reduction of multi-dimensional interval type-2 (IT2) fuzzy sets (FSs). We utilize the Karnik-Mendel (KM) algorithm to estimate the centroid boundary of a multi-dimensional footprint of uncertainty (FOU). We deal with two-dimensional (2-D) fuzzy sets as we can visualize the FOU using 3-D plots, thus making the illustration of the methods simple. However, the basic idea can be extended to multiple dimensions. We give a formal definition of the centroid boundary of a 2-D IT2 fuzzy membership function (FMF) and propose two methods for its estimation. The first method computes embedded type-1 (T1) FSs whose centroids constitute the centroid boundary. We obtain the embedded sets by producing slices of the domain using different sets of parallel planes and then apply the KM algorithm over each slice, to obtain “embedded-curves.” For the second method, we approximate our first method by restricting embedded-curves to be “embedded-lines” thus enhancing computational speed. These type reduction techniques can be applied to applications involving multi-dimensional centroid estimation such as, clustering, support vector estimation for dimensionality reduction, fuzzy logic controllers, to mention a few.","PeriodicalId":408343,"journal":{"name":"2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125400416","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