• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1993.06a
• /
• pp.1155-1158
• /
• 1993

Proficiency in creating a knowledge base is required for high accuracy fuzzy control. To overcome this a fuzzy inference method is proposed that take these membership functions from the probability densities showing the distribution of the mesurement values. And a method using a rough fuzzy knowledge base automatically created from the basic measurement data and tuned using the gradient method is proposed. In actual tests, these were applied to automatic high accuracy adjustment devices for magnetic head and for high frequency circuits with good results.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.4 no.2
• /
• pp.138-153
• /
• 2010

The interactions between people who do not know each other have been greatly increased with the on-going increase of people's cyberspace activities. In this situation, there exist potential risk factors such as the possibility of fraud, so we need a method to reduce or eliminate those risk factors. Concerning this necessity, rating systems are widely used, and many trust metrics calculated from rate values that people give to each other are proposed to help them make decisions. However, the trust metrics decrease the accuracy, and this is caused by the different rating scales and ranges of each person. So, we propose a fuzzy adjustment method to solve this problem. It is possible to catch the exact meaning of the trust value that each person selects through applying fuzzy sets, which improve the accuracy of the trust metric calculated from the trust values. We have applied our fuzzy adjustment method to the TidalTrust algorithm, a representative algorithm for calculating the local scalar trust metric, and we performed an experimental evaluation with four data sets and three evaluation methods.

• Journal of Institute of Control, Robotics and Systems
• /
• v.4 no.4
• /
• pp.448-457
• /
• 1998

A neural network based control algorithm with fuzzy compensation is proposed for the automated adjustment in the production of electronic end-products. The process of adjustment is to tune the variable devices in order to examine the specified performances of the products ready prior to packing. Camcorder is considered as a target product. The required test and adjustment system is developed. The adjustment system consists of a NNC(neural network controller), a sub-NNC, and an auxiliary algorithm utilizing the fuzzy logic. The neural network is trained by means of errors between the outputs of the real system and the network, as well as on the errors between the changing rate of the outputs. Control algorithm is derived to speed up the learning dynamics and to avoid the local minima at higher energy level, and is able to converge to the global minimum at lower energy level. Many unexpected problems in the application of the real system are resolved by the auxiliary algorithms. As the adjustments of multiple items are related to each other, but the significant effect of performance by any specific item is not observed. The experimental result shows that the proposed method performs very effectively and are advantageous in simple architecture, extracting easily the training data without expertise, adapting to the unstable system that the input-output properties of each products are slightly different, with a wide application to other similar adjustment processes.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2002.04a
• /
• pp.486-490
• /
• 2002

When the fuzzy controller apply to a real plant, We have not excepted result of a satisfactory control by modeling error and lacking information about an plant. In this case, we have to adjust the scale factors for improvement of the control performance and this method need a lot of time and cost for perform a trial and error. In this paper, we proposed the fuzzy controller with the automatic adjustment of scaling factors. It was improve upon the control performance using a adequate scale factor by fuzzy logic and normalizer. As the results of simulation through the second order plant, we confirmed that the proposed the fuzzy controller within the function of automatic scale get a good response compare with the fuzzy controller within the fixed scale factor.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.41 no.9
• /
• pp.1095-1103
• /
• 1992

An approach to fuse the fuzzy inference system which is able to deal with imprecise and uncertain information and genetic algorithms which display the excellent robustness in complex optimization problems is presented in this paper. In order to combine genetic algorithms and fuzzy inference engine effectively the new reasoning method is suggested. The efficient identification method of fuzzy rules is proposed through the adjustment of search areas of genetic algorithms. The feasibilty of the proposed approach is evaluated through simulation.

• Journal of Korean Society of Steel Construction
• /
• v.9 no.4 s.33
• /
• pp.579-588
• /
• 1997

During the construction of cable stayed bridge, errors are always caused by various reasons, accumulated and amplified through the complex construction steps. It is likely that the undesirable stress distribution of members and the large deflection of the bridge different from design values come out The adjustment of cables during construction is absolutely indispensable to correct the stress distribution of the members and the geometrical configuration of the bridge. In the conventional method, weight coefficients are used to consider the difference of units between cable forces and girder deflections during the optimization process of cable adjustment. However, it is not easy to determine weight coefficients and the adjustment must be repeated several times with the time consuming process of the determination of new weight coefficients in case that errors are out of design allowable limits. In this paper, fuzzy linear regression analysis is applied to the cable adjustment to overcome those problems. In the application of fuzzy linear regression analysis method the designer's intention and the design allowable limits can be formulated in the form of the constraints of the linear optimization problem. Therefore, the cable adjustment in construction site can be carried out with the fuzzy linear regression analysis more rapidly than with the convetional method.

• Journal of the Korea Society of Computer and Information
• /
• v.10 no.5 s.37
• /
• pp.11-16
• /
• 2005

Recently, there are a lot of endeavor to implement a fuzzy theory to artificial neural network. Goh proposed the fuzzy single layer perceptron algorithm and advanced fuzzy perceptron based on the generalized delta rule to solve the XOR Problem and the classical Problem. However, it causes an increased amount of computation and some difficulties in application of the complicated image recognition. In this paper, we propose an enhanced fuzzy single layer Perceptron using the dynamic adjustment of threshold. This method is applied to the XOR problem, which used as the benchmark in the field of pattern recognition. The method is also applied to the recognition of digital image for image application. In a result of experiment, it does not always guarantee the convergence. However, the network show improved the learning time and has the high convergence rate.

• Nuclear Engineering and Technology
• /
• v.53 no.11
• /
• pp.3665-3674
• /
• 2021

One of the important parts of the in-core fuel management is loading pattern optimization (LPO). The loading pattern optimization as a reasonable design of the in-core fuel management can improve both economic and safe aspects of the nuclear reactor. This work proposes the hybrid of fuzzy logic controller with harmony search algorithm (HS) for loading pattern optimization in a pressurized water reactor. The music improvisation process to find a pleasing harmony is inspiring the harmony search algorithm. In this work, the adjustment of the harmony search algorithm parameters such as the bandwidth and the pitch adjustment rate are increasing performance of the proposed algorithm which is done through a fuzzy logic controller. Hence, membership functions and fuzzy rules are designed to improve the performance of the HS algorithm and achieve optimal results. The objective of the method is finding an optimum core arrangement according to safety and economic aspects such as reduction of power peaking factor (PPF) and increase of effective multiplication factor (Keff). The proposed approach effectiveness has been tried in two cases, Michalewicz's bivariate function problem and NEACRP LWR core. The results show that by using fuzzy harmony search algorithm the value of the fitness function is improved by 15.35%. Finally, with regard to the new solutions proposed in this research it could be used as a trustworthy method for other optimization issues of engineering field.

• Journal of Korea Multimedia Society
• /
• v.20 no.8
• /
• pp.1464-1471
• /
• 2017

One of the important factors in game design is difficulty adjustment. An appropriate level of difficulty makes users have a sense of challenge and interest. However, the adjustment of difficulty takes a lot of time and effort, because of its ambiguity. To solve the problem, we propose a difficulty control method using a fuzzy theory. In this paper, a simple demonstration is exemplified to verify the effectiveness of our method. Experimental results show that the difficulty of the game changes according to the user's skill.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2001.10a
• /
• pp.80-84
• /
• 2001

When the fuzzy controller apply to a real plant, We have not excepted result of a satisfactory control by modeling error and lacking information about an plant. In this case, we have to adjust the control factors for improvement of the control performance and this method need a lot of time and cost for perform a trial and error. In this paper, we proposed the fuzzy regulator with the automatic adjustment of scaling factors. It was improve upon the control performance using a adequate scale factor by fuzzy inference. We implemented the controller using the DSP processor and applied in a hydraulic servo system. And then we observed an experimental results.