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2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)最新文献

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Fuzzy knowledge representation in cognitive cities 认知城市中的模糊知识表示
2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2015-12-01 DOI: 10.1109/FUZZ-IEEE.2015.7337951
Patrick Kaltenrieder, Edy Portmann, Thomas Myrach
{"title":"Fuzzy knowledge representation in cognitive cities","authors":"Patrick Kaltenrieder, Edy Portmann, Thomas Myrach","doi":"10.1109/FUZZ-IEEE.2015.7337951","DOIUrl":"https://doi.org/10.1109/FUZZ-IEEE.2015.7337951","url":null,"abstract":"This paper gives an insight into cognitive computing for smart cities, resulting in cognitive cities. Cognitive cities and cognitive computing research with the underlying concepts of knowledge graphs and fuzzy cognitive maps are presented and supported by existing tools (i.e., IBM Watson and Google Now) and intended tools (meta-app). The paper illustrates FCM as a suiting instrument to represent information/knowledge in a city environment driven by human-technology interaction, enforcing the concept of cognitive cities. A proposed paper prototype combines the findings of the paper and shows the next step in the implementation of the proposed meta-app.","PeriodicalId":185191,"journal":{"name":"2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125320280","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
Semi-supervised fuzzy C-means clustering for change detection from multispectral satellite image 基于半监督模糊c均值聚类的多光谱卫星图像变化检测
2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2015-11-30 DOI: 10.1109/FUZZ-IEEE.2015.7337978
D. Mai, L. Ngo
{"title":"Semi-supervised fuzzy C-means clustering for change detection from multispectral satellite image","authors":"D. Mai, L. Ngo","doi":"10.1109/FUZZ-IEEE.2015.7337978","DOIUrl":"https://doi.org/10.1109/FUZZ-IEEE.2015.7337978","url":null,"abstract":"Data clustering has been applied in almost areas such as health, natural resource management, urban planning... especially, fuzzy clustering which the advantage with handling better for ambiguous data. This paper proposes a method of improving fuzzy c-means clustering algorithm by using the criteria to move the prototype of clusters to the expected centroids which are pre-determined on the basis of samples. The proposed algorithm is used for a model of change detection on multispectral satellite imagery at multiple temporals. The experiments are implemented on various data sets in comparison with other approaches.","PeriodicalId":185191,"journal":{"name":"2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"114 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127192397","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: 35
A fuzzy link-based approach for XML information retrieval 基于模糊链接的XML信息检索方法
2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2015-11-30 DOI: 10.1109/FUZZ-IEEE.2015.7338017
M'hamed Mataoui, Faouzi Sebbak, F. Benhammadi, Kadda Beghdad Bey
{"title":"A fuzzy link-based approach for XML information retrieval","authors":"M'hamed Mataoui, Faouzi Sebbak, F. Benhammadi, Kadda Beghdad Bey","doi":"10.1109/FUZZ-IEEE.2015.7338017","DOIUrl":"https://doi.org/10.1109/FUZZ-IEEE.2015.7338017","url":null,"abstract":"The increasing amount of available XML documents collections has led to the emergence of new challenges in information retrieval field. Therefore, multiple sources of evidence were used to retrieve XML elements at different levels of granularity. XML information retrieval combines textual and structural information to perform different information retrieval tasks. In this paper, we propose a new approach exploiting link evidence to re-rank XML retrieval results. Our approach, based on fuzzy logic concepts, combines both content and link evidence for all retrieved XML elements. The combination process generates a new ranked list from the initial returned list. Experiment based on INEX 2007 Wikipedia collection showed improvement of the interpolated precision values.","PeriodicalId":185191,"journal":{"name":"2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"6 10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127363075","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
A component-based object detection method extended with a fuzzy inference engine 一种基于模糊推理引擎的构件对象检测方法
2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2015-11-30 DOI: 10.1109/FUZZ-IEEE.2015.7337917
Murat Koyuncu, Basar Cetinkaya
{"title":"A component-based object detection method extended with a fuzzy inference engine","authors":"Murat Koyuncu, Basar Cetinkaya","doi":"10.1109/FUZZ-IEEE.2015.7337917","DOIUrl":"https://doi.org/10.1109/FUZZ-IEEE.2015.7337917","url":null,"abstract":"In this paper, we propose a component-based object detection method extended with the fuzzy inference technique. The proposed method detects constituent components of a complex object instead of a whole object in images. For component detection, multiple multi-class support vector machines (SVM) are used in parallel. Each SVM classifies the candidate component using a different low-level image feature. The obtained results are fused to reach a decision about the component. Then, a fuzzy object extractor determines the whole object considering the detected components and their geometric configurations. The fuzzy object extractor is a fuzzy inference engine which tests various combinations of detected components and their fuzzified directions and distances. The initial tests yield promising results and encourage further studies to extend proposed method.","PeriodicalId":185191,"journal":{"name":"2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127484648","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 comparative analysis for multi-attribute decision making methods: TOPSIS, AHP, VIKOR using intuitionistic fuzzy sets 基于直觉模糊集的TOPSIS、AHP、VIKOR多属性决策方法的比较分析
2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2015-11-30 DOI: 10.1109/FUZZ-IEEE.2015.7338059
F. Dammak, Leila Baccour, A. Alimi
{"title":"A comparative analysis for multi-attribute decision making methods: TOPSIS, AHP, VIKOR using intuitionistic fuzzy sets","authors":"F. Dammak, Leila Baccour, A. Alimi","doi":"10.1109/FUZZ-IEEE.2015.7338059","DOIUrl":"https://doi.org/10.1109/FUZZ-IEEE.2015.7338059","url":null,"abstract":"Intuitionistic fuzzy sets (IFSs) are used in methods of multi-criteria decision making. Some techniques are used in each method to use intuitionistic fuzzy information. Therefore, crisp methods can be changed to use IFSs information. The latter are used in Technique for order performance by similarity to ideal solution (TOPSIS), Analytic Hierarchy Process (AHP) and in VIKOR. We apply These methods in Human Capital Indicators (HCI) [1] and we compare them to distinguish differences between used techniques.","PeriodicalId":185191,"journal":{"name":"2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114931532","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
Interactive sound generation for relaxation based on heartbeat and brain wave 基于心跳和脑电波的互动声音产生放松
2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2015-11-30 DOI: 10.1109/FUZZ-IEEE.2015.7338031
Y. Maeda
{"title":"Interactive sound generation for relaxation based on heartbeat and brain wave","authors":"Y. Maeda","doi":"10.1109/FUZZ-IEEE.2015.7338031","DOIUrl":"https://doi.org/10.1109/FUZZ-IEEE.2015.7338031","url":null,"abstract":"Recently, the research and development of the system which is able to obtain the relaxation effect have been actively performed. Most of the moderns have some stresses and require the request for healing, and the early development of the relaxation system is expected. For example, in the system which sounds and images are presented to the user, the relaxation effect is judged from the vital signals of heartbeat, pulse rate and so on, and the contents of presentation is tuned to raise its effect has been developed. In this research, we aim to construct the system to adjust the automatic operation to obtain the relaxation effect by presenting the sound to the user, and judging the degree of relaxation based on the heartbeat and the brain wave information. In this paper, as an advance research on the construction of this system, we try to analyze the features of the heartbeat (electrocardiogram) and brain wave (electroencephalogram) measured in a different state and find the index that judges the relaxation degree.","PeriodicalId":185191,"journal":{"name":"2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116108707","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
Interval Type-2 fuzzy C-Means approach to collaborative clustering 区间型-2模糊c均值协同聚类方法
2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2015-11-30 DOI: 10.1109/FUZZ-IEEE.2015.7337932
Trong Hop Dang, L. Ngo, W. Pedrycz
{"title":"Interval Type-2 fuzzy C-Means approach to collaborative clustering","authors":"Trong Hop Dang, L. Ngo, W. Pedrycz","doi":"10.1109/FUZZ-IEEE.2015.7337932","DOIUrl":"https://doi.org/10.1109/FUZZ-IEEE.2015.7337932","url":null,"abstract":"There have been numerous studies on using the FCM algorithm in clustering and collaboration clustering, especially in data analysis, data mining and pattern recognition. In this study, we present new methods involving interval Type-2 fuzzy sets to realize collaborative clustering. Data in which the clustering results realized at one data site impact clustering carried out at other data sites. Those methods endowed with interval type-2 fuzzy sets help cope with uncertainties present in data. The experiment with weather data sets has shown better results in comparison with the previous approaches.","PeriodicalId":185191,"journal":{"name":"2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128664501","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
Combined model of customer assessment for order acceptance problem under fuzzy goals and fuzzy constraints 模糊目标和模糊约束下的订单接受问题客户评价组合模型
2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2015-11-30 DOI: 10.1109/FUZZ-IEEE.2015.7338052
A. Aliabadi, H. Berenji
{"title":"Combined model of customer assessment for order acceptance problem under fuzzy goals and fuzzy constraints","authors":"A. Aliabadi, H. Berenji","doi":"10.1109/FUZZ-IEEE.2015.7338052","DOIUrl":"https://doi.org/10.1109/FUZZ-IEEE.2015.7338052","url":null,"abstract":"Customer assessment plays an important role in make to order production systems for ranking of the orders. This paper extents α-cut and interactive Fuzzy Multi-Objective Linear Programming combine approaches for solving the imprecise customer assessment for order acceptance problem under price breaks with fuzzy goals and fuzzy constraints with linear Membership Function. The proposed combined approach aims to simultaneously minimize the storage cost, pay delay time, conflict rate and transportation cost. The fifth objective function maximize the total value of purchasing. This combined approach enables decision maker to interactively modify fuzzy coefficients and constraints until attained both an efficient compromise solution and increase overall decision maker satisfaction degree. Additionally, the proposed combination approach provides a systematic framework that facilitates the fuzzy decision-making process. The fuzzy combined approach was utilized on an industrial case, and findings will be shown.","PeriodicalId":185191,"journal":{"name":"2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129328009","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
Developing a novel multi-fusion brain-computer interface (BCI) system with particle swarm optimization for motor imagery task 开发一种基于粒子群优化的运动想象任务多融合脑机接口系统
2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2015-11-30 DOI: 10.1109/FUZZ-IEEE.2015.7337842
Tsung-Yu Hsieh, Yang-Yin Lin, Yu-Ting Liu, Chieh-Ning Fang, Chin-Teng Lin
{"title":"Developing a novel multi-fusion brain-computer interface (BCI) system with particle swarm optimization for motor imagery task","authors":"Tsung-Yu Hsieh, Yang-Yin Lin, Yu-Ting Liu, Chieh-Ning Fang, Chin-Teng Lin","doi":"10.1109/FUZZ-IEEE.2015.7337842","DOIUrl":"https://doi.org/10.1109/FUZZ-IEEE.2015.7337842","url":null,"abstract":"In this paper, we develop a novel multi-fusion brain-computer interface (BCI) based on linear discriminant analysis (LDA) to deal with motor imagery (MI) classification problem. We combine filter bank and sub-band common spatial pattern (SBCSP) to extract features from EEG data in the preprocessing phase, and then LDA classifiers are applied to classify brain activities to identify either left or right hand imagery. To further foster the performance of the proposed system, a fuzzy integral (FI) approach is employed to fuse information sources, and particle swarm optimization (PSO) algorithm is exploited to globally update parameters in the fusion structure. Consequently, our experimental results indicate that the proposed system provides superior performance compared to other approaches.","PeriodicalId":185191,"journal":{"name":"2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130403615","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
Inductive learning based on rough set theory for medical decision making 基于粗糙集理论的医疗决策归纳学习
2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2015-11-30 DOI: 10.1109/FUZZ-IEEE.2015.7338075
A. Azar, N. Bouaynaya, R. Polikar
{"title":"Inductive learning based on rough set theory for medical decision making","authors":"A. Azar, N. Bouaynaya, R. Polikar","doi":"10.1109/FUZZ-IEEE.2015.7338075","DOIUrl":"https://doi.org/10.1109/FUZZ-IEEE.2015.7338075","url":null,"abstract":"This paper proposes an algorithm that uses inductive learning and rough set theory (ILRS) to analyze the clinical data available in a patient file (records). A typical patient file has unstructured (both descriptive and quantitative) information that is also uncertain and sometimes incomplete. Successful clinical treatments depend on correct medical diagnosis which determines the correct set of variables or features causing a certain pathology. Clinical applications are by no means the only applications that require decision-making with reasoning from a large and incomplete amount of information. We show that the proposed ILRS technique is able to reduce the available number of features into a smaller core set that precisely describes the information system. We can also quantitatively evaluate the level of dependence of the considered pathology, or decision feature, on a given set of condition features or attributes. Moreover, we show that the proposed algorithm is able to cope with uncertain and incomplete information. We consider a case study of an incomplete information system obtained during cannulation of radial and dorsalis pelis arteries. We show how ILRS succeeds to remove redundancy and determine the most significant condition attributes for a given set of decision attributes from contaminated data with uncertainty. A multi-class classification with preference relations is presented through a set of decision rules. Unlike statistical analysis of clinical data, the reliability of the proposed ILRS algorithm is independent of the data size.","PeriodicalId":185191,"journal":{"name":"2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123352642","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
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