• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.2
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• pp.292-297
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• 2013

Nowadays, a strategy of the self-optimizing machining process is an imperative approach to improve the product quality and increase productivity of manufacturing systems. This paper presents a concept of self-optimizing forming system that allows the forming system automatically to adjust the forming parameters online for guarantee the product quality and avoiding the machine stop. An intelligent monitoring system that has the functions of observation, evaluation and diagnostic is developed to evaluate the pully quality during forming process. Any abnormal variation of forming machining parameters could be detected and adjusted by an intelligent control system aiming to maintain the machining stability and the desired product quality. This approach is being practiced on the pully forming machine for evaluating the efficiency of the proposed strategy.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.262-271
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• 2003

Specification of reinforcement method was suggested according to the ground condition and tunnelling environment such as adjacent building and surface settlement. Tunnel database consists of 8 different groups of data according to the tunnel construction situations and major problems of ground. A tunnel countermeasure expert system based on client/server system was developed with on-line. The expert system provides proper solution to the each construction sites backing up the information of the tunnelling and ground information through Internet. The effective factors of tunnel construction were shown by the analyzing relationship and partial relationship between face stability and RMR factors. This study will be very helpful to make the most of in-situ data and suggest proper applicability of tunnel reinforcement system escaping from the dependence of some experienced experts for the absent of guide.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.2
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• pp.73-79
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• 2013

Cloud computing is a form which provides IT resources through network and pays the cost as much as you used. And it has advantages that it doesn't need to construct infrastructure and can be offered a variety of environments. The main core of these computing is virtualization technology. Security mechanism about attacks using vulnerabilities of virtualization technology isn't provided right and existing security tools can't be applied as it is. In this paper, we proposed honeyVM structure that can cope actively by collecting the information about attacks using virtualization vulnerability. Mamdani fuzzy inference is used to adjust dynamically the number of formed honeyVM depending on the load of system. Security structure to protect actual virtual machine from attacks and threats is proposed. The performance of the proposed structure in this paper measured occurred attack detection rate and resource utilization rate.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.1
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• pp.42-46
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• 2009

Das et al. [EJOR 117(1999) 100-112] discussed the real valued solution procedure of the multiobjective transportation problem(MOTP) where the cost coefficients of the objective functions, and the source and destination parameters have been expressed as interval values by the decision maker. In this note, we consider the interval valued solution procedure of the same problem. This problem has been transformed into a classical multiobjective transportation problem where the constraints with interval source and destination parameters have been converted into deterministic ones. Numerical examples have been provided to illustrate the solution procedure for this case.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.1
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• pp.59-64
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• 2010

To improve system performance, we apply the concept of membership function to Variance Considered Machines (VCMs) which is a modified algorithm of Support Vector Machines (SVMs) proposed in our previous studies. Many classification algorithms separate nonlinear data well. However, existing algorithms have ignored the fact that probabilities of error are very high in the data-mixed area. Therefore, we make our algorithm ignore data which has high error probabilities and consider data importantly which has low error probabilities to generate system output according to the probabilities of error. To get membership function, we calculate sigmoid function from the dataset by considering means and variances. After computation, this membership function is applied to the VCMs.

• Journal of the Korean Society for Railway
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• v.16 no.4
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• pp.272-277
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• 2013

Power quality is a term that is now extensively used in power systems applications, and in this context the voltage, current, and phase angle are discussed widely. In particular, different algorithms that are capable of detecting the voltage sag and swell information in a real time environment have been proposed and developed. Voltage sag and swell play an important role in determining the stability, quality, and operation of a power system. This paper presents ANFIS (Adaptive Network based Fuzzy Inference System) models with different membership functions to build the voltage shape with the knowledge of known system parameters, and detect voltage sag and swell accurately. The performance of each method has been compared with each other/other methods to determine the effectiveness of the different models, and the results are presented.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.105-110
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• 1998

본 논문에서는 퍼지 로직을 이용하여 ATM 망의 ABR(Available Bit Rate) 트래픽 제어를 위한 효과적이고, 안정적인 피드백 제어 알고리즘을 제안한다. 기존 알고리즘들의 단점을 보완하면서, 망 내의 상황이 변하더라도 자가 학습 기능(self-learning capability)을 이용하여 파라미터 값들을 상황에 맞게 변화시키는 퍼지 로직을 이용한 새로운 제어알고리즘을 제안한다. 제안된 알고리즘은 Projection algorithm을 이용하여, 과거의 데이터로부터 다음 순간의 ABR 버퍼의 크기를 예측하며 퍼지 제어기의 출력 함수 파라미터들은 성능함수를 최소화하도록 학습된다. 제안된 알고리즘은 안정성(stability)이 보장되며, Upstream bottleneck 환경등의 특수하고, 제한된 상태에서도, 요구되는 QoS와 max-min fairness가 만족되고, 링트 효율을 극대화 할 수 있음을 시뮬레이션을 통하여 입증한다.

• Earthquakes and Structures
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• v.22 no.4
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• pp.421-430
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• 2022

This paper addresses the stochastic control problem of robots within the framework of parameter uncertainty and uncertain noise covariance. First of all, an open circle deterministic trajectory optimization issue is explained without knowing the unequivocal type of the dynamical framework. Then, a Linear Quadratic Gaussian (LQG) controller is intended for the ostensible trajectory-dependent linearized framework, to such an extent that robust hereditary NN robotic controller made out of the Kalman filter and the fuzzy controller is blended to ensure the asymptotic stability of the non-continuous controlled frameworks. Applicability and performance of the proposed algorithm shown through simulation results in the complex systems which are demonstrate the feasible to improve the performance by the proposed approach.

• Journal of information and communication convergence engineering
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• v.21 no.3
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• pp.198-207
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• 2023

Responding to changes in artificial intelligence models and the data environment is crucial for increasing data-learning accuracy and inference stability of industrial applications. A learning model that is overfitted to specific training data leads to poor learning performance and a deterioration in flexibility. Therefore, an early stopping technique is used to stop learning at an appropriate time. However, this technique does not consider the homogeneity and independence of the data collected by heterogeneous nodes in a differential network environment, thus resulting in low learning accuracy and degradation of system performance. In this study, the generalization performance of neural networks is maximized, whereas the effect of the homogeneity of datasets is minimized by achieving an accuracy of 99.7%. This corresponds to a decrease in delay time by a factor of 2.33 and improvement in performance by a factor of 2.5 compared with the conventional method.

• Ocean Systems Engineering
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• v.14 no.1
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• pp.73-84
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• 2024

In order to achieve the best performance, the automatic control with advanced technology is made of sheathed steel to withstand a wide range of wave loads. This model shows how to control the vibration of the fiber panel as a solution using the new results from the Lyapunov stability question, a modification of the bat that making it easy to calculate and easy to use. It is used to reduce the storage space required in this system. The results show that the planned worker can compensate effectively for the unplanned delay. The results show that the proposed controller can compensate for delays and errors. Fuzzy control (predictive control) demonstrated the external vibration can be reduced.