• Journal of the Korea Society of Computer and Information
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• v.14 no.7
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• pp.9-15
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• 2009

The fuzzy weighted mean classifier is one of the most common classification models and could achieve high performance by adjusting the weights. However, the weights were generally decided based on the experience of experts, which made the resulting classifiers to suffer the lack of consistency and objectivity. To resolve this problem, in this paper, a weight deciding method based on the statistics of the data is introduced, which ensures the learned classifiers to be consistent and objective. To investigate the effectiveness of the proposed methods, Iris data set available from UCI machine learning repository is used and promising results are obtained.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.189-192
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• 2001

In this paper, we propose a ADALINE controller using fuzzy-backpropagation algorithm to adjust weight. In the proposed ADALINE controller, using fuzzy algorithm for traning neural network, controller make use of ADALINE due to simple and computing efficiency. This controller includes adaptive learning rate to accelerate teaming. It applies to servo-motor as an controlled process. And then it take a simulation for the position control, so the verify the usefulness of the proposed ADALINE controller.

• Journal of Korean Society for Quality Management
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• v.21 no.2
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• pp.194-214
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• 1993

This paper purports to study on interactive fuzzy goal programming model which leads to the compromise solution which the decision maker satisfies through the interactive approach. We also attempted to calculate local proxy preference function from utility function of sum-of-logarithms in connection with marginal rate of substitution and interactive approach for the purpose of applying weight of multiobjective function. In an attempt to grasp compromise solution from fuzzy efficient solution, we decided to take the interactive method and presented stopping rule for this.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.464-465
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• 2008

This paper proposed a robust controller in order to handle the boom vibration of inspection robot. While a inspection robot moves on boom with vibration by weight occurs. Therefore, Boom as structure like cantilever beam appears vibration by weight of inspection robot. The Z axis of inspection robot operates with Sliding structure. inspection robot is used "Fuzzy Controller" for position control with Z axis. The developed robot system is composed of the specially designed car for inspection robot. The proposed Fuzzy Controllers are used to track position reference signal of Z axis. A Experiment verify that the proposed Fuzzy Controller design method can achieve favorable control performance with regard to external disturbance.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.1254-1263
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• 1993

Representing knowledge uncertainty , aggregating evidence confidences , and propagation uncertainties are three key elements that effect the ability of a rule-based expert system to represent domains with uncertainty . Fuzzy set theory provide a good mathematical tool for representing the vagueness associated with a variable when , as the condition of a rule , it only partially corresponds to the input data. However, the aggregation of ANDed and Ored confidences is not as simple as the intersection and union operators defined for fuzzy set membership. There is, in fact, a certain degree of compensation that occurs when an expert aggregates confidences associated with compound evidence . Further, expert often consider individual evidences to be varying importance , or weight , in their support for a conclusion. This paper presents a flexible approach for evaluating evidence and conclusion confidences. Evidences may be represented as fuzzy or nonfuzzy variables with as associat d degree of certainty . different weight can also be associated degree of certainty. Different weights can also be assigned to the individual condition in determining the confidence of compound evidence . Conclusion confidence is calculated using a modified approach combining the evidence confidence and a rule strength. The techniques developed offer a flexible framework for representing knowledge and propagating uncertainties. This framework has the potention to reflect human aggregation of uncertain information more accurately than simple minimum and maximum operator do.

• Tunnel and Underground Space
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• v.14 no.4
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• pp.275-286
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• 2004

It is studied to select the reinforcement method of an abandoned tunnel which are intersected under the new roadway line. In the various decision makings, the reasonability for the reinforcement method of an abandoned tunnel was estimated using the pair-wise comparison and the fuzzy approximate reasoning to simplify the process of survey research. And there is reflected all the qualitative and quantitative characterizations by investigation items. In order to select the reinforcement method of an abandoned tunnel, 4 characteristic factors of construction, economical efficiency, safety and maintenance were used. Using the simple survey research and pair-wise comparison matrix, the weight of 4 factors was decided. The fuzzy approximate reasoning was used to calculate the quantitative value of each factor And then reflecting each weight to these results, the final reinforcement method of an abandoned tunnel could be determined.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.1
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• pp.10-18
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• 2003

In this paper, we proposed a learning algorithm for the ADALINE network. The proposed algorithm exploits fuzzy system for automatic tuning of the weight parameters of the ADALINE network. The inputs of the fuzzy system are error and change of error, and the output is the weight variation. We used different scaling factor for each weights. In order to verify the effectiveness of the proposed algorithm, we peformed the simulation and experimentation for the cases of the noise cancellation and the inverted pendulum control. The results show that the proposed algorithm does not need the learning rate and improves 4he performance compared to the Widrow-Hoff delta rule for ADALINE.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.918-932
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• 2021

Evaluation of the collaboration of the upstream and downstream enterprises in the manufacturing supply chain is important to improve their synergistic effect. From the supply chain perspective, this study establishes the evaluation model of the manufacturing enterprise collaboration on the basis of fuzzy entropy according to synergistic theory. Downstream enterprises carry out coordinated capital, business, and information flows as subsystems and research enterprises as composite systems. From the three subsystems, the collaboration evaluation index is selected as the order parameter. The compound fuzzy matter-element matrix is established by using its improved algorithm. Subordinate membership and standard deviation fuzzy matter-element matrixes are constructed. Index weight is determined using the entropy weight method. The closeness of each matter element is then calculated. Through a representative of the home appliance industry, namely, Gree Electric Appliances Inc. of Zhuhai, empirical analysis of data in 2011-2017 from the company and its upstream and downstream enterprise collaboration shows a good trend, but the coordinated development has not reached stability. Gree Electric Appliances Inc. of Zhuhai need to strengthen the synergy with upstream and downstream enterprises in terms of cash, business, and information flows to enhance competitiveness. Experimental results show that this method can provide precise suggestions for enterprises, improve the degree of collaboration, and accelerate the development and upgrading of the manufacturing industry.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.121-123
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• 2021

Image processing is being used in various forms in important fields of the 4th industrial revolution, such as artificial intelligence, smart factories, and the IoT industry. In particular, in systems that require data processing such as object tracking, medical images, and object recognition, noise removal is used as a preprocessing step, but the existing algorithm has a drawback in that blurring occurs in the filtering process. Therefore, in this paper, we propose a filter algorithm using switching fuzzy weights. The proposed algorithm switches the fuzzy function by dividing the low-frequency region and the high-frequency region by the standard deviation of the filtering mask, and obtains the final output according to the fuzzy weight. The proposed algorithm showed improved results compared to the existing method, and showed excellent characteristics in the region where the high-frequency component is strong.

• Steel and Composite Structures
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• v.51 no.5
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• pp.473-485
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• 2024

This paper proposes a composite form of fuzzy adaptive control plan based on a robust observer. The fuzzy 2D control gains are regulated by the parameters in the LMIs. Then, control and learning performance indices with weight matrices are constructed as the cost functions, which allows the regulation of the trade-off between the two performance by setting appropriate weight matrices. The design of 2D control gains is equivalent to the LMIs-constrained multi-objective optimization problem under dual performance indices. By using this proposed smart tracking design via fuzzy nonlinear criterion, the data link can be further extended. To evaluate the performance of the controller, the proposed controller was compared with other control technologies. This ensures the execution of the control program used to track position and trajectory in the presence of great model uncertainty and external disturbances. The performance of monitoring and control is verified by quantitative analysis. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and control theory.