• Journal of the Institute of Electronics Engineers of Korea CI
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• 제38권4호
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• pp.1-9
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• 2001

In this paper, we propose Fuzzy M/M/1/K queueing network model which has derived by appling the fuzzy set theory to M/M/l/K queueing network model in which has single server and system capacity K. When the arriving rate of input job and the servicing rate of a server arc represented as the linguistic attributes, the system analysis can be performed by using this model. The major evaluation measures of system such as the average number of jobs existing in the system, the average number of jobs into system, and the average spending time of job in system etc. are derived for the evaluation of system. Computer simulation was performed for verifying the effectiveness of these result equations. In which the various fuzzy arriving rates and fuzzy servicing rates according to varying the system capacity K were given for the system evaluation. We verified that the results of simulation are in accord with the expected evaluations in the proposed fuzzy model.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제13권2호
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• pp.181-189
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• 2013

In this paper, we introduce the fuzzy neural network based on the individual input space to design the pattern recognizer. The proposed networks configure the network by individually dividing each input space. The premise part of the networks is independently composed of the fuzzy partition of individual input spaces and the consequence part of the networks is represented by polynomial functions. The learning of fuzzy neural networks is realized by adjusting connection weights of the neurons in the consequent part of the fuzzy rules and it follows a back-propagation algorithm. In addition, in order to optimize the parameters of the proposed network, we use real-coded genetic algorithms. Finally, we design the optimized pattern recognizer using the experimental data for pattern recognition.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• 제35권11호
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• pp.983-989
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• 2007

The bird strike simulation is a problem characterized by a high degree of uncertainty. It deals with nonlinear dynamics, complicated models of bird materials and geometry, as well as a plenty of possible boundary and initial conditions. In this complex field, uncertainty management plays an important role. This paper aims to assess the effect of input uncertainty of bird strike analysis on the impact behavior of the leading edge of the WIG(Wing in Ground Effect) craft obtained with finite element analysis using LS-DYNA 3D. The uncertainties of the bird strike simulation arise due to imprecision or lack of information, due to variability or scatter, or as a consequence of model simplification. These uncertain parameters are represented by fuzzy numbers with their membership functions quantifying an initial guess for the actual value of the model parameter. Using the transformation method as a special implementation of fuzzy arithmetic, the model can be analyzed with the intention of determining the influence of each uncertain parameter on the overall bird strike behavior.

• Journal of Korea Water Resources Association
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• 제35권5호
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• pp.619-629
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• 2002

Water in the atmosphere is circulated by reciprocal action of various factors in the climate system. Otherwise, any climate phenomenon could not occur of itself. Thus, we have tried to understand the climate change by analysis of the factors. In this study, the fuzzy theory which is useful to express inaccurate and approximate nature in the real world is used for forecasting precipitation influenced by the factors. Forecasting models used in this study are neuro-fuzzy system and a Markov chain and those are applied to precipitation forecasting of illinois. Various atmosphere circulation factors(like soil moisture and temperature) influencing the climate change are considered to forecast precipitation. As a forecasting result, it can be found that the considerations of the factors are helpful to increase the forecastibility of the models and the neuro-fuzzy system gives us relatively more accurate forecasts.

• Journal of KIISE:Software and Applications
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• 제29권4호
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• pp.278-288
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• 2002

This paper presents a design and implementation of fuzzy retrieval system that could support an associated learning in problem banks. It tries to retrieve some of the problems conceptually related to specific semantics described by user's queries. In particular, the problem retrieval system employs a fuzzy thesaurus which represents relationships between domain dependent vocabularies as fuzzy degrees. It would keep track of characteristics of the associated learning, which should guarantee high recall and acceptable precision for retrieval effectiveness. That is, since the thesaurus could make a vocabulary mismatch problem resolved among query terms and document index terms, this retrieval system could take a chance to effectively support user's associated teaming. Finally, we have evaluated whether the fuzzy retrieval system is appropriate for the associated teaming or not, by means of its precision and recall rate point of view.

• Journal of the Korean Institute of Intelligent Systems
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• 제13권6호
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• pp.667-672
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• 2003

In this paper, we propose a systematic method for intelligent digital redesign of a fuzzy-model-based controller for continuous-time nonlinear dynamical systems which may also contain uncertainties. The continuous-time uncertain TS fuzzy model is first constructed to represent the uncertain nonlinear systems. An extended parallel distributed compensation(EPDC) technique is then used to design a fuzzy-model-based controller for both stabilization and tracking. The designed continuous-time controller is then converted to an equivalent discrete-time controller by using an integrated intelligent digital redesign method. This new design technique provides a systematic and effective framework for integration of the fuzzy-model-based control theory and the advanced digital redesign technique for nonlinear dynamical systems with uncertainties. Finally, The single link flexible-joint robot arm is used as an illustrative example to show the effectiveness and the feasibility of the developed design method.

• Journal of the Korean Institute of Intelligent Systems
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• 제21권1호
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• pp.12-18
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• 2011

In this paper, we proposed Interval Type-2 polynomial Radial Basis Function Neural Networks. In the receptive filed of hidden layer, Interval Type-2 fuzzy set is used. The characteristic of Interval Type-2 fuzzy set has Footprint Of Uncertainly(FOU), which denotes a certain level of robustness in the presence of un-known information when compared with the type-1 fuzzy set. In order to improve the performance of proposed model, we used the linear polynomial function as connection weight of network. The parameters such as center values of receptive field, constant deviation, and connection weight between hidden layer and output layer are optimized by Conjugate Gradient Method(CGM) and Space Search Evolutionary Algorithm(SSEA). The proposed model is applied to gas furnace dataset and its result are compared with those reported in the previous studies.

• Journal of the Korean Institute of Intelligent Systems
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• 제19권5호
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• pp.595-602
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• 2009

Fuzzy rules, which represent the behavior of their system, are sensitive to fuzzy clustering techniques. If the classification abilities of such clustering techniques are improved, their systems can work for the purpose more accurately because the capabilities of the fuzzy rules and parameters are enhanced by the clustering techniques. Thus, this paper proposes a new hierarchically structured clustering algorithm that can enhance the classification abilities. The proposed clustering technique consists of two clusters based on correlationship and statistical characteristics between data, which can perform classification more accurately. In addition, this paper uses difference data sets to reflect the patterns and regularities of the original data clearly, and constructs multiple fuzzy systems to consider various characteristics of the differences suitably. To verify effectiveness of the proposed techniques, this paper applies the constructed fuzzy systems to the field of time series prediction, and performs prediction for nonlinear time series examples.

• Archives of design research
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• 제14권4호
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• pp.5-14
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• 2001

Among Human Sensibility-oriented products a gap between the images that designers try to express through that product and users emotional evaluation becomes an issue. The data on the correlation between image words used for design evaluation and images used in the design process are especially significant. This study based on these correlations suggests a Fuzzy retrieval system supporting styling design with images and image words. In the system, the relational data are demonstrated by Fuzzy thesaurus as correlation coefficient from the degree of similarity among image words. And the degree of similarity is produced based on image evaluation. Image retrieval is conducted by the algorithm of Fuzzy thesaurus development, 1) among image words, 2) images to image words, 3) image words to images and 4) among images: 4 different modes are provided as retrieval modes. Also transfer between modes is carried by direct operating interface, therefore divergent thinking and convergent thinking is supported well. The system consists of operation for the gap and the measurement unit of emotional evaluation, and visualization units. Under unified interface environments are set in order for consistency of the operation.

• Journal of Intelligence and Information Systems
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• 제10권2호
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• pp.91-109
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• 2004

This study investigates the effectiveness of a hybrid approach using fuzzy sets that describe approximate phenomena of the real world. Compared to the other existing techniques, the approach handles inexact knowledge in common linguistic terms as human reasoning does it. Integration of fuzzy sets with case-based reasoning (CBR) is important in that it helps to develop a successful system far dealing with vague and incomplete knowledge which statistically uses membership value of fuzzy sets in CBR. The preliminary results show that the accuracy of the integrated fuzzy-CBR approach proposed for this study is higher that of conventional techniques. Our proposed approach is applied to corporate bond rating of Korean companies.