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1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228)

4-9 May 1998

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  • The 1998 IEEE International Conference on Fuzzy Systems Proceedings [front matter]

    Publication Year: 1998, Page(s):i - xxiv
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  • Fuzzy Sets Based Global Evaluation in the Metal Cutting Process Planning

    Publication Year: 1998, Page(s):897 - 902
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (707 KB)

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  • An interval approach to clustering

    Publication Year: 1998, Page(s):1464 - 1469
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (486 KB)

    Generally, a linguistic expression attributed to a given situation is represented by a fuzzy set characterized by a membership function. The /spl alpha/ level of this function is an interval. Therefore the notion of interval is implicit in the definition of a fuzzy set relative to the linguistic expression. Thus, the coding by interval is justified. However, the utilization of intervals is not res... View full abstract»

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  • A Fuzzy Phonetic ModuIe for Speech Synthesis from Text

    Publication Year: 1998, Page(s):1512 - 1517
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  • Author's index

    Publication Year: 1998, Page(s):A_1 - A_3
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  • A new fuzzy-fractal-genetic method for automated mathematical modelling and simulation of robotic dynamic systems

    Publication Year: 1998, Page(s):1182 - 1187 vol.2
    Cited by:  Papers (20)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (568 KB)

    We describe a computer program for mathematical modelling and simulation (MMS) of robotic dynamic systems (RDS) using fuzzy logic techniques, genetic algorithms and fractal theory. The computer program combines soft computing (SC) techniques with mathematical methods and can be considered as an intelligent system for the domain of modelling and simulation of robotic systems. The computer program s... View full abstract»

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  • Detection of traffic anomalies using fuzzy logic based techniques

    Publication Year: 1998, Page(s):1176 - 1181 vol.2
    Cited by:  Papers (1)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (472 KB)

    Traffic incident detection involves both the collection and analysis of traffic data. The paper discusses the development of a novel time-indexed traffic anomaly detection algorithm. A unique partition of time into the “type of day”, and “time of day” is performed. Using this partition, a novel fuzzy neuromorphic unsupervised learning algorithm is used to calibrate the &ldq... View full abstract»

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  • Building a concise decision table for fuzzy rule induction

    Publication Year: 1998, Page(s):997 - 1002 vol.2
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (420 KB)

    Fuzzy systems that can automatically derive fuzzy if then rules and membership functions from numeric data have been developed previously. In this paper, we propose two new fuzzy learning methods for automatically deriving membership functions and fuzzy if-then rules from a set of given training examples. The proposed methods first select relevant attributes and build appropriate initial membershi... View full abstract»

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  • Hierarchical fuzzy logic traffic control at a road junction using genetic algorithms

    Publication Year: 1998, Page(s):1170 - 1175 vol.2
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (444 KB)

    Traffic control at a road junction by a complex fuzzy logic controller is investigated. The increase in the complexity of junction means more number of input variables must be taken into account, which will increase the number of fuzzy rules in the system. A hierarchical fuzzy logic controller is introduced to reduce the number of rules. Besides, the increase in the complexity of the controller ma... View full abstract»

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  • Product pricing decision support fuzzy systems through the Internet

    Publication Year: 1998, Page(s):1664 - 1669 vol.2
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (508 KB)

    The extremely fast development of software tools in the last few years has opened a completely new perspective for computing systems. The emergence of commuting languages such as Perl and Java has made possible the development of online systems running as cross-platform programs. We present an example of such systems: a commuting system for cost analysis. The system provides an analysis of the cos... View full abstract»

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  • Information retrieval systems: where is the fuzz?

    Publication Year: 1998, Page(s):1367 - 1372 vol.2
    Cited by:  Papers (2)
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    If the field of fuzzy information systems is to grow and mature, it is imperative to define terms precisely. For the sub-field of information retrieval, we attempt to clarify the definition of some terms and discuss the possible sources of fuzziness within this sub-field. Moreover, we discuss the implications that this has in terms of defining flexible information retrieval models and propose an a... View full abstract»

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  • Massively parallel fuzzy systems: the case of three spiral pattern recognition

    Publication Year: 1998, Page(s):1066 - 1071 vol.2
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (480 KB)

    The main objectives of this paper are: 1) to describe the working of a massively parallel fuzzy system; 2) to test the system on a new benchmark-the three spiral data set; and 3) to describe the behaviour of the system when solving the problem. The system described is aimed at solving pattern recognition problems in real-time. Pattern recognition data are subjected to non-iterative decision making... View full abstract»

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  • An improvement of neuro-fuzzy learning algorithm for tuning fuzzy rules based on fuzzy clustering method

    Publication Year: 1998, Page(s):991 - 996 vol.2
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (424 KB)

    Based on the fuzzy clustering method, we improve a neuro-fuzzy learning algorithm. In this improved approach, before learning fuzzy rules we extract typical data from training data by using the fuzzy c-means clustering algorithm, in order to remove redundant data and resolve conflicts in data, and make them as practical training data. By these typical data, fuzzy rules can be tuned by using the ne... View full abstract»

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  • Freeway traffic incident detection using fuzzy CMAC neural networks

    Publication Year: 1998, Page(s):1164 - 1169 vol.2
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    We present a new approach of incident detection based on a novel network architecture called the Fuzzy CMAC, and a feature extraction pre-processing algorithm using the nonlinear Karhunen-Loeve (K-L) transformation. We prove that the Fuzzy CMAC architecture is an excellent universal approximator that is able to learn an arbitrary traffic pattern discriminating function to any degree of accuracy wi... View full abstract»

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  • An agglomerative technique for Pearson Type II mixture decomposition with applications

    Publication Year: 1998, Page(s):1400 - 1405 vol.2
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    Mixture modeling can be considered as the probabilistic counterpart of fuzzy clustering. Gaussian mixtures are the most widely used distributions in mixture modeling and the expectation maximization (EM) algorithm is commonly used for Gaussian mixture decomposition. Gaussian mixtures are not suitable for certain problems. Moreover, the EM algorithm suffers from the disadvantage that the number of ... View full abstract»

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  • Adaptive fuzzy edge detector for image enhancement

    Publication Year: 1998, Page(s):1542 - 1547 vol.2
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    A novel adaptive fuzzy edge detector for image enhancement, which can work well in full range of random impulse noise probability and perform efficiently in the environment of mixed Gaussian impulse noise, is proposed. It is an extended adaptive weighted fuzzy mean (EAWFM) filter, which combines adaptive weighted fuzzy mean filter and fuzzy normed inference system to efficiently perform edge detec... View full abstract»

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  • Generalized adaptive defuzzifier

    Publication Year: 1998, Page(s):1680 - 1683 vol.2
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    A generalized adaptive defuzzifier (GAD) is proposed. GAD consists of two parts: (1) a rule firing engine (RFE) which fires only the rules whose firing strengths are equal to or greater than a prespecified threshold, and (2) a rule aggregation engine (RAE) which combines the fired rules with a modified version of the center of gravity (COG) defuzzifier. GAD is more general so that COG and mean of ... View full abstract»

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  • Supervision of fuzzy controllers using genetic algorithms

    Publication Year: 1998, Page(s):1241 - 1246 vol.2
    Cited by:  Papers (1)
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    The fast growth of fuzzy control applications in industry, together with the need of getting increasingly efficient control systems, has been the motivation for the development of approaches to the supervision of fuzzy controllers. Some novel approaches to this problem encompass the application of artificial intelligence techniques, such as the utilization of neural networks and genetic algorithms... View full abstract»

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  • Inversion of fuzzy models-practical issues

    Publication Year: 1998, Page(s):1658 - 1663 vol.2
    Cited by:  Papers (5)
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    This paper deals with some practical issues of the inversion of nonlinear static systems described by fuzzy models. We derive an analytical expression of the derivatives of a fuzzy mapping and we use it in an optimization based inversion algorithm. We discuss some practical aspects of this algorithm, including the inversion of multiple-input, multiple-output (MIMO) fuzzy systems. We also demonstra... View full abstract»

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  • A fuzzy deductive object-oriented database model

    Publication Year: 1998, Page(s):1361 - 1366 vol.2
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    Object-oriented and deductive database models are two different paradigms in database modeling. As has been pointed out by many researchers, each of these data models has its shortcomings when dealing with database/knowledge-base applications. Therefore, it is believed that combining object-oriented concepts with those of deductive database modeling results in a powerful data model especially for ... View full abstract»

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  • Neural activation ratio based fuzzy reasoning

    Publication Year: 1998, Page(s):1217 - 1222 vol.2
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (540 KB)

    Presents a class of binary neural nets which seem to be similar to the natural neural nets concerning topological and functional issues. It is the medium activity among the neurons in a given neural area which represents the “amplitude” of the associated variable, making the net insensitive to individual errors. It is proved that fuzzy reasoning is an emergent property of such nets, if... View full abstract»

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  • Xfuzzy: a design environment for fuzzy systems

    Publication Year: 1998, Page(s):1060 - 1065 vol.2
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (484 KB)

    Xfuzzy is a CAD tool that eases the development of fuzzy systems from their conception to their final implementation. It is composed of a set of modules and programs that share a common specification language and cover the different stages of the design process. Modules for describing, verifying and tuning the behavior of the system are integrated within the environment. In addition to these featu... View full abstract»

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  • A synthesis of fuzzy rule-based system verification

    Publication Year: 1998, Page(s):985 - 990 vol.2
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    We give a synthesis of methods proposed in literature that try to extend the verification of classical rule bases to the case of fuzzy knowledge modeling. We identify two dual lines of thought respectively leading to static and dynamic anomaly detection methods. The major outcome of the confrontation between both approaches is that their results, stated in terms of necessary and/or sufficient cond... View full abstract»

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  • Rules of chaotic behaviour extracted from a fuzzy-neural network

    Publication Year: 1998, Page(s):1159 - 1163 vol.2
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    The paper presents a fuzzy-neuro architecture called FuNN (fuzzy-neural network) along with a structural learning algorithm based on backpropagation with forgetting. The FuNN structure is adaptable and it can automatically capture the main characteristics and the underlying rules of the problem. Adaptation includes both the membership functions and rules of the fuzzy system. The key point of the p... View full abstract»

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  • Fuzzy clustering by quadratic regularization

    Publication Year: 1998, Page(s):1394 - 1399 vol.2
    Cited by:  Papers (25)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (460 KB)

    A quadratic regularization method is proposed as a variation of the fuzzy c-means. The standard fuzzy c-means is regarded as a regularization of the crisp k-means, and hence other regularization methods can be studied as fuzzy versions of the crisp c-means. A new algorithm for calculating membership values is derived, whereas calculation of cluster centers is similar to the standard method. The ne... View full abstract»

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