• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2000.08a
• /
• pp.189-192
• /
• 2000

A fuzzy controller for the evaluation of the quantization parameters in the H.263 coder has been introduced. We adopted a Mamdani fuzzy controller with centroid defuzzification. The inputs are variance, entropy, current motion vector and previous motion vector. This results is obtained a effective rate control technique using fuzzy Quantization.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.49.5-49
• /
• 2001

The Proportional-Integral-Derivative control scheme is widely used in industries. This paper investigates an alternative control paradigm for controlling lightweight Cartesian robot arms. Fuzzy PI control is used and validated experimentally by comparing performance with a conventional PID control algorithm. The results show the effectiveness of the fuzzy PI control. The fuzzy control shows superior performance in transient response over the conventional one.

• Journal of KIISE:Information Networking
• /
• v.31 no.3
• /
• pp.289-297
• /
• 2004

State-of-the-art wireless communication networks allow dynamic relocation of mobile terminals. A location management mechanism is required to keep track of a mobile terminal for delivering incoming calls. In this paper, we propose a fuzzy logic-based selective paging method to reduce paging cost. In the proposed fuzzy logic-based location management method, the location update uses the area-based method that uses direction-based together with movement-based methods, and the location search uses the fuzzy logic-based selective paging method based on the mobility information of mobile terminals. A partial candidate paging area is selected by fuzzy control rules, then the fuzzy logic-based selective paging method pages only the cells within the partial candidate paging area. The performance of proposed fuzzy logic-based location management method is to be evaluated by both an analytical model and a simulation, and is compared with those of LA and BVP methods. From these evaluation results, we know that the proposed fuzzy logic-based location management method provide better performance than other location management methods.

• Journal of the Korea Convergence Society
• /
• v.9 no.7
• /
• pp.231-240
• /
• 2018

Automobile industry is facing a variety of risks, including the rise of international oil price and the increase of car prices. In addition to the government's deregulation, efforts should be made to improve management aiming at higher production efficiency. In this study, we established a model for evaluating the procurement logistics based on the Fuzzy-AHP-TOPSIS by using the factors that are actually used in real companies aimed at the improvement of procurement logistics. A total of three automobile factories of Company G were chosen as the evaluation subject. In the result of the Fuzzy-AHP analysis that was conducted on a sample of three car factories, solving the long-term quality problems, minimizing the stop time due to the shortage of materials, preventing the of equipment accident, and solving the short-term quality problems were proven to be the most important factors. TOPSIS analysis result indicated that Factory B had the best procurement logistics. Our study has significance that it can contribute to the improvement of efficiency in the automobile industry as the evaluation model suggested in this study can be used for regular evaluation related to the procurement logistics in the future.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.1
• /
• pp.32-40
• /
• 2008

Fuzzy rules are very useful and efficient to describe classification rules especially when the attribute values are continuous and fuzzy in nature. However, it is generally difficult to determine membership functions for generating efficient fuzzy classification rules. In this paper, we propose a method of automatic generation of efficient fuzzy classification rules using evolutionary algorithm. In our method we generate a set of initial membership functions for evolutionary algorithm by supervised clustering the training data set and we evolve the set of initial membership functions in order to generate fuzzy classification rules taking into consideration both classification accuracy and rule comprehensibility. To reduce time to evaluate an individual we also propose an evolutionary algorithm with data partition evaluation in which the training data set is partitioned into a number of subsets and individuals are evaluated using a randomly selected subset of data at a time instead of the whole training data set. We experimented our algorithm with the UCI learning data sets, the experiment results showed that our method was more efficient at average compared with the existing algorithms. For the evolutionary algorithm with data partition evaluation, we experimented with our method over the intrusion detection data of KDD'99 Cup, and confirmed that evaluation time was reduced by about 70%. Compared with the KDD'99 Cup winner, the accuracy was increased by 1.54% while the cost was reduced by 20.8%.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.21 no.45
• /
• pp.225-235
• /
• 1998

The scientific evaluation on enterprise helps establishing better management policy. Financial index has been used for the enterprise evaluation as the objective data. However, the necessity of the subjective data for competitive power evaluation is advocated recently. Therefore, in this paper, we propose an evaluation model of competitive power on enterprise by fuzzy integral, using the objective and the subjective data. The evaluation factors are composed to the financial index, top management, product, organization and enterprise's environment. These factors are grouped by detailed sub-factors of 16 units. Lastly, utilizing these factors, the efficiency of this method was shown by the result of the case study of 10 manufacturing enterprises.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.10 no.4
• /
• pp.275-280
• /
• 2010

Verification of efficiency in data management fuzzy entropy and similarity measure were discussed and verified by applying reliable data selection problem and numerical data similarity evaluation. In order to calculate the certainty or uncertainty fuzzy entropy and similarity measure are designed and proved. Designed fuzzy entropy and similarity are considered as dissimilarity measure and similarity measure, and the relation between two measures are explained through graphical illustration. Obtained measures are useful to the application of decision theory and mutual information analysis problem. Extension of data quantification results based on the proposed measures are applicable to the decision making and fuzzy game theory.

• Journal of Korean Society for Quality Management
• /
• v.24 no.3
• /
• pp.133-144
• /
• 1996

In order to evaluate the effectiveness of fuzzy reasoning to sensory tests, in this paper, a non-linear fuzzy system model that can estimate the general evaluator obtained from a numerical example of test of taste is constructed. And the applicability of fuzzy reasoning to sensory test is discussed on the basis of errors occurred from the estimates in combination of attributes of objects and from the results of multi-regression analysis. This paper proved that fuzzy reasoning using fuzzy If-then rules is applicable to sensory test.

• Journal of the Korean Society of Safety
• /
• v.20 no.1 s.69
• /
• pp.126-132
• /
• 2005

The purpose of this study is to propose a method to evaluate task complexity using CIFs(Complexity Influencing Factors). We developed a method that CIFs can be used in the evaluation of task complexity using fuzzy linguistic approach. That is, a fuzzy linguistic multi-criteria method to assess task complexity in a specific task situation was proposed. The CIFs luting was assessed in linguistic terms, which are described by fuzzy numbers with triangular and trapezoidal membership function. A fuzzy weighted average algorithm, based on the extension principle, was employed to aggregate these fuzzy numbers. Finally, the method was validated by experimental approach. In the result, it was validated that TCIM(Tink Complexity Index Method) is an efficient method to evaluate task complexity because the correlation coefficient between task performance time and TCI(Task Complexity Index) was 0.699.

• Speech Sciences
• /
• v.7 no.3
• /
• pp.167-183
• /
• 2000

In this paper, we propose two kinds of chaos dimensions, the fuzzy correlation and fuzzy Lyapunov dimensions, for speaker recognition. The proposal is based on the point that chaos enables us to analyze the non-linear information contained in individual's speech signal and to obtain superior discrimination capability. We confirm that the proposed fuzzy chaos dimensions play an important role in enhancing speaker recognition ratio, by absorbing the variations of the reference and test pattern attractors. In order to evaluate the proposed fuzzy chaos dimensions, we suggest speaker recognition using the proposed dimensions. In other words, we investigate the validity of the speaker recognition parameters, by estimating the recognition error according to the discrimination error of an individual speaker from the reference pattern.