2010 Annual Meeting of the North American Fuzzy Information Processing Society最新文献_第6页

FuzzyProbSim: Fuzzy probability as similarity measure FuzzyProbSim:模糊概率作为相似性度量

2010 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2010-07-12 DOI: 10.1109/NAFIPS.2010.5548188

A. Ralescu, S. Visa, Stefana Popovici

引用次数: 0

Towards a new justification of the Tastle-Wierman (TW) dissention and consensus measures (and their potential role in education) 对Tastle-Wierman (TW)分歧和共识措施的新论证(及其在教育中的潜在作用)

2010 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2010-07-12 DOI: 10.1109/NAFIPS.2010.5548273

K. Villaverde, O. Kosheleva

引用次数: 4

An improved genetic algorithm for robust fuzzy clustering with unknown number of clusters 未知簇数的鲁棒模糊聚类改进遗传算法

2010 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2010-07-12 DOI: 10.1109/NAFIPS.2010.5548175

A. Banerjee

{"title":"An improved genetic algorithm for robust fuzzy clustering with unknown number of clusters","authors":"A. Banerjee","doi":"10.1109/NAFIPS.2010.5548175","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548175","url":null,"abstract":"In this paper the problem of partitioning noisy data when the number of clusters c is not known a priori is revisited. The methodology proposed is a population-based search in the partition space using a genetic algorithm. Potential solutions are represented using a two-part representation scheme, where the first part of the chromosome represents the classification of the data into true (retained) and outlier (trimmed) sets, and the second part is the result of a partition on the true set for a particular value of c, which is simultaneously optimized by the process. A two-tier fitness function is also proposed in this paper, one which first assesses potential solutions on the basis of a test of clustering tendency on the retained set, and later on the efficacy of the partition for a given value of c. A mating pool is created out of highly successful individuals from the test of clustering tendency and allowed to crossover and produce offspring solutions which inherit the better partition from either of its parents. The proposed methodology is an improvement over a multi-objective genetic algorithm-based clustering technique, which previously was shown to be superior (or at least comparable) to robust clustering methods that assume a known value of c.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126716617","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

Extending maximum entropy techniques to entropy constraints 将最大熵技术扩展到熵约束

2010 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2010-07-12 DOI: 10.1109/NAFIPS.2010.5548264

G. Xiang, V. Kreinovich

{"title":"Extending maximum entropy techniques to entropy constraints","authors":"G. Xiang, V. Kreinovich","doi":"10.1109/NAFIPS.2010.5548264","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548264","url":null,"abstract":"In many practical situations, we have only partial information about the probabilities. In some cases, we have crisp (interval) bounds on the probabilities and/or on the related statistical characteristics. In other situations, we have fuzzy bounds, i.e., different interval bounds with different degrees of certainty. In a situation with uncertainty, we do not know the exact value of the desired characteristic. In such situations, it is desirable to find its worst possible value, its best possible value, and its “typical” value – corresponding to the “most probable” probability distribution. Usually, as such a “typical” distribution, we select the one with the largest value of the entropy. This works perfectly well in usual cases when the information about the distribution consists of the values of moments and other characteristics. For example, if we only know the first and the second moments, then the distribution with the largest entropy if the normal (Gaussian) one. However, in some situations, we know the entropy (= amount of information) of the distribution. In this case, the maximum entropy approach does not work, since all the distributions which are consistent with our knowledge have the exact sam e entropy value. In this paper, we show how the main ideas of the maximum entropy approach can be extended to this case.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128206857","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

A generalization on the approximation of compact fuzzy sets 关于紧模糊集逼近的一种推广

2010 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2010-07-12 DOI: 10.1109/NAFIPS.2010.5548417

Y. Chalco-Cano, H. Romaan-Flores, A. Flores-Franulic

引用次数: 1

Aspects of object merging 对象合并的几个方面

2010 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2010-07-12 DOI: 10.1109/NAFIPS.2010.5548205

A. Bronselaer, Guy De Trea

引用次数: 13

Nonlinear ant system for large scale search spaces 大规模搜索空间的非线性蚁群系统

2010 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2010-07-12 DOI: 10.1109/NAFIPS.2010.5548409

Pooia Lalbakhsh, Bahram Zaeri, M. Fesharaki

{"title":"Nonlinear ant system for large scale search spaces","authors":"Pooia Lalbakhsh, Bahram Zaeri, M. Fesharaki","doi":"10.1109/NAFIPS.2010.5548409","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548409","url":null,"abstract":"In this paper we focus on linearity and nonlinearity of learning schemes applied in ant colony optimization algorithms and discuss about the consequences of the two approaches on the overall algorithm's performance and efficiency. The paper reviews the previously proposed ACO algorithms, talking about the underlying linear philosophy of most of them, and proposes a nonlinear learning scheme by which not only a new flexible view is introduced on ACO, the performance metrics are also considerably improved regarding large scale search spaces. After a theoretical discussion on both linearity and nonlinearity, we applied the nonlinear learning scheme on the travelling salesman problem based on large scale graphs up to 9500 nodes. The simulation is accomplished between the ACS algorithm and the nonlinear method called NLAS on identical randomly generated graphs, to evaluate the performance metrics such as branching factor which implies the algorithm exploration and the generated best tour length which shows the algorithm convergence towards the global optimum. As simulation results show, considerable improvements in the overall convergence and exploration in the nonlinear approach is achieved.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125333534","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

Fuzzy ontology for natural language 自然语言的模糊本体

2010 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2010-07-12 DOI: 10.1109/NAFIPS.2010.5548416

Julia Taylor Rayz, V. Raskin

引用次数: 35

Type-2 fuzzy sets and bichains 2型模糊集与双链

2010 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2010-07-12 DOI: 10.1109/NAFIPS.2010.5548265

J. Harding, C. Walker, E. Walker

引用次数: 1

Linguisitc representation of Nash equilibriums in fuzzy games 模糊对策中纳什均衡的语言表示

2010 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2010-07-12 DOI: 10.1109/NAFIPS.2010.5548187

Setareh Sharifian, Alireza Chakeri, F. Sheikholeslam

引用次数: 10