2009 IEEE International Conference on Fuzzy Systems最新文献_第8页

Different sequential clustering algorithms and sequential regression models 不同的顺序聚类算法和顺序回归模型

2009 IEEE International Conference on Fuzzy Systems Pub Date : 2009-10-02 DOI: 10.1109/FUZZY.2009.5277183

S. Miyamoto, Kenta Arai

引用次数: 14

Domestic robot service based on ontology applying environmental information 基于环境信息的本体家政机器人服务

2009 IEEE International Conference on Fuzzy Systems Pub Date : 2009-10-02 DOI: 10.1109/FUZZY.2009.5277187

Y. Fukusato, S. Sakurai, Siliang Wang, E. Sato-Shimokawara, Toru Yamaguchi

引用次数: 8

Push communication for network robot services and RSi/RTM interoperability 推进网络机器人业务通信和RSi/RTM互操作性

2009 IEEE International Conference on Fuzzy Systems Pub Date : 2009-10-02 DOI: 10.1109/FUZZY.2009.5277188

M. Narita, Y. Murakawa, Chuzo Akiguchi, Y. Kato, Toru Yamaguchi

引用次数: 13

Lattice-valued fuzzy turing machines and their computing power 格值模糊图灵机及其计算能力

2009 IEEE International Conference on Fuzzy Systems Pub Date : 2009-10-02 DOI: 10.1109/FUZZY.2009.5277362

Yongming Li

{"title":"Lattice-valued fuzzy turing machines and their computing power","authors":"Yongming Li","doi":"10.1109/FUZZY.2009.5277362","DOIUrl":"https://doi.org/10.1109/FUZZY.2009.5277362","url":null,"abstract":"In this paper, fuzzy Turing machines with membership degrees in distributive lattices, which are called lattice-valued fuzzy Turing machines, are studied. First several formulations of lattice-valued fuzzy Turing machines, including in particular deterministic and nondeterministic lattice-valued fuzzy Turing machines (l-DTMcs and l-NTMs), are given. It is shown that l-DTMcs and l-NTMs are not equivalent as the acceptors of fuzzy languages. This contrasts sharply with classical Turing machines. Second, it is shown that lattice-valued fuzzy Turing machines can recognize n-r.e. sets in the sense of Bedregal and Figueira, the super-computing power of fuzzy Turing machines is established in the lattice-setting. Third, it is demonstrated that the truth-valued lattice being finite is a necessary and sufficient condition for the existence of a universal lattice-valued fuzzy Turing machine. For an infinite distributive lattice with a compact metric, it is declared that a universal fuzzy Turing machine exists in an approximate sense. This means, for any prescribed accuracy, there is a universal machine that can simulate any lattice-valued fuzzy Turing machine on it with the given accuracy.","PeriodicalId":117895,"journal":{"name":"2009 IEEE International Conference on Fuzzy Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129938347","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

Complexity, interpretability and explanation capability of fuzzy rule-based classifiers 模糊规则分类器的复杂性、可解释性和解释能力

2009 IEEE International Conference on Fuzzy Systems Pub Date : 2009-10-02 DOI: 10.1109/FUZZY.2009.5277380

H. Ishibuchi, Y. Kaisho, Y. Nojima

引用次数: 22

Chemical vapor deposition quality prediction system based on support vector regression and fuzzy learning mechanism 基于支持向量回归和模糊学习机制的化学气相沉积质量预测系统

2009 IEEE International Conference on Fuzzy Systems Pub Date : 2009-10-02 DOI: 10.1109/FUZZY.2009.5277281

J. Su, Ching-Shun Chen

{"title":"Chemical vapor deposition quality prediction system based on support vector regression and fuzzy learning mechanism","authors":"J. Su, Ching-Shun Chen","doi":"10.1109/FUZZY.2009.5277281","DOIUrl":"https://doi.org/10.1109/FUZZY.2009.5277281","url":null,"abstract":"In advanced semiconductor manufacturing, the in-process wafers need to be monitored periodically in order to obtain high stability and high yield rate. However, the actual measurement is usually obtained after all the work-pieces of the same lot have been processed. The parameter drift or shift of the production equipment could not be detected in real-time thereby increasing the production cost. We proposed a quality prediction system (QPS) based on support vector regression (SVR) and fuzzy learning mechanism (FLM) to overcome this problem. The SVR provided good generalization performance for prediction, and the embedded FLM implied a continuous improvement or at least non-degradation of the system performance in an ever changing environment. The effectiveness of the proposed QPS was validated by test on chemical vapor deposition (CVD) process in practical 12-inch wafer fabrication. The results show that the proposed QPS not only fulfills real-time quality measurement of each wafer, but also detects the performance degradation of the corresponding machines from the information of manufacturing process.","PeriodicalId":117895,"journal":{"name":"2009 IEEE International Conference on Fuzzy Systems","volume":"304 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134152514","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

Evolution of cooperative behavior in a spatial iterated prisoner's dilemma game with different representation schemes of game strategies 不同博弈策略表征下空间迭代囚徒困境博弈中合作行为的演化

2009 IEEE International Conference on Fuzzy Systems Pub Date : 2009-10-02 DOI: 10.1109/FUZZY.2009.5277282

H. Ishibuchi, Hiroyuki Ohyanagi, Y. Nojima

{"title":"Evolution of cooperative behavior in a spatial iterated prisoner's dilemma game with different representation schemes of game strategies","authors":"H. Ishibuchi, Hiroyuki Ohyanagi, Y. Nojima","doi":"10.1109/FUZZY.2009.5277282","DOIUrl":"https://doi.org/10.1109/FUZZY.2009.5277282","url":null,"abstract":"The iterated prisoner's dilemma (IPD) game has been frequently used to examine the evolution of cooperative behavior among agents in the field of evolutionary computation. A number of factors are known to be related to the evolution of cooperative behavior. One well-known factor is spatial relations among agents. The IPD game is often played in a grid-world. Such a spatial IPD game has a neighborhood structure which is used for local opponent selection in the IPD game and local parent selection in genetic operations. Another important factor is the choice of a representation scheme to encode each strategy. Different representation schemes often lead to totally different results. Whereas the choice of a representation scheme is known to be important, a mixture of different representation schemes has not been examined for the spatial IPD game in the literature. This means that a population of homogeneous agents with the same representation scheme has been assumed. In this paper, we introduce a different situation to the spatial IPD game in order to examine the evolution of cooperative behavior under more general assumptions. The main novelty of our spatial IPD game is the use of a mixture of different representation schemes. This means that we use a population of inhomogeneous agents with different representation schemes. Another novelty is the use of two neighborhood structures, each of which is used for local opponent selection and local parent selection. Under these specifications, we show a number of interesting observations on the evolution of cooperative behavior.","PeriodicalId":117895,"journal":{"name":"2009 IEEE International Conference on Fuzzy Systems","volume":"5 10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132344418","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

Generating single granularity-based fuzzy classification rules for multiobjective genetic fuzzy rule selection 多目标遗传模糊规则选择中基于单粒度的模糊分类规则生成

2009 IEEE International Conference on Fuzzy Systems Pub Date : 2009-10-02 DOI: 10.1109/FUZZY.2009.5277369

R. Alcalá, Y. Nojima, F. Herrera, H. Ishibuchi

{"title":"Generating single granularity-based fuzzy classification rules for multiobjective genetic fuzzy rule selection","authors":"R. Alcalá, Y. Nojima, F. Herrera, H. Ishibuchi","doi":"10.1109/FUZZY.2009.5277369","DOIUrl":"https://doi.org/10.1109/FUZZY.2009.5277369","url":null,"abstract":"Recently, multiobjective evolutionary algorithms have been applied to improve the difficult tradeoff between interpretability and accuracy of fuzzy rule-based systems. It is known that both requirements are usually contradictory, however, these kinds of algorithms can obtain a set of solutions with different trade-offs. The application of multiobjective evolutionary algorithms to fuzzy rule-based systems is often referred to as multiobjective genetic fuzzy systems. The first study on multiobjective genetic fuzzy systems was multiobjective genetic fuzzy rule selection in order to simultaneously achieve accuracy maximization and complexity minimization. This approach is based on the generation of a set of candidate fuzzy classification rules by considering a previously fixed granularity or multiple fuzzy partitions with different granularities for each attribute. Then, a multiobjective evolutionary optimization algorithm is applied to perform fuzzy rule selection. Although the multiple granularity approach is one of the most promising approaches, its interpretability loss has often been pointed out. In this work, we propose a mechanism to generate single granularity-based fuzzy classification rules for multiobjective genetic fuzzy rule selection. This mechanism is able to specify appropriate single granularities for fuzzy rule extraction before performing multiobjective genetic fuzzy rule selection. The results show that the performance of the obtained classifiers can be even improved by avoiding multiple granularities, which increases the linguistic interpretability of the obtained models.","PeriodicalId":117895,"journal":{"name":"2009 IEEE International Conference on Fuzzy Systems","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132095975","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: 19

Dynamic system identification using recurrent neural network with multi-valued connection weight 基于多值连接权的递归神经网络动态系统辨识

2009 IEEE International Conference on Fuzzy Systems Pub Date : 2009-10-02 DOI: 10.1109/FUZZY.2009.5277240

A. Thammano, Phongthep Ruxpakawong

引用次数: 1

Fuzzification of discrete attributes from financial data in fuzzy classification trees 模糊分类树中金融数据离散属性的模糊化

2009 IEEE International Conference on Fuzzy Systems Pub Date : 2009-10-02 DOI: 10.1109/FUZZY.2009.5277400

Keeley A. Crockett, Z. Bandar, J. O'Shea

{"title":"Fuzzification of discrete attributes from financial data in fuzzy classification trees","authors":"Keeley A. Crockett, Z. Bandar, J. O'Shea","doi":"10.1109/FUZZY.2009.5277400","DOIUrl":"https://doi.org/10.1109/FUZZY.2009.5277400","url":null,"abstract":"Fuzzy Decision Trees have been successfully applied to both classification and regression problems by allowing gradual transitions to exist between attribute values. Methodologies for fuzzification in fuzzy trees currently create such gradual transitions for continuous attributes. This is achieved by automatically creating fuzzy regions around tree nodes using an optimization algorithm or by using the knowledge of a human expert to create a series of fuzzy sets which are representative of the attributes domain. A problem occurs when trying to construct a fuzzy tree from real world data which comprises of only discrete or a mixture of discrete and continuous attributes. Discrete attribute values have no proximity to other values in the decision space, as there is no continuum between values. Consequently, within a fuzzy tree they are interpreted as crisp sets and contribute little towards the final outcome. This paper proposes a new approach for the fuzzification of discrete attributes in fuzzy decision trees. The approach ranks discrete values on the basis of their effect on the outcome rate and assigns a possibility of being a specific outcome. Experiments carried out on two real world financial datasets which contain a significant proportion of discrete attributes show improved classification accuracy compared with a crisp interpretation of such attributes within fuzzy trees.","PeriodicalId":117895,"journal":{"name":"2009 IEEE International Conference on Fuzzy Systems","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134473851","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