• Journal of applied mathematics & informatics
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• v.42 no.2
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• pp.379-390
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• 2024

This study proposes a fuzzy inventory model for managing large-scale production, incorporating cost considerations. The model accounts for two types of expenditure scenarios-parametric and exponential. Uncertainty surrounds holding costs, setup costs, and demand rates. The approach considers a supply chain system with a complex manufacturing process, factoring in transportation costs based on the quantity of goods and distance between the supplier and retailer. The initial crisp model is then transformed into a fuzzy simulation, incorporating specific fuzzy variables affecting inventory costs. The proposed method significantly reduces overall inventory costs for the entire supply chain. Retailer demand is linked to inventory levels, and vendor/distributor storage deteriorates over time. The fuzzy condition assumes hexagonal variables for all associated factors. The study employs the signed distance method for defuzzification to determine the optimal order quantity with hexagonal fuzzy numbers. Mathematical examples are provided to illustrate the practicality of the proposed approach.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.615-620
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• 2001

This paper addresses the design of sliding model fuzzy-model-based controller using genetic algorithms. In general, the construction of fuzzy logic controllers has difficulties for the lack of systematic design procedure. To release this difficulties, the sliding model fuzzy-model-based controllers was presented by authors. In this proposed method, the fuzzy model, which represents the local dynamic behavior of the given nonlinear system, is utilized to construct the controller. The overall controller consists of the local compensators which compensate the local dynamic linear model and the feed-forward controller which is designed via sliding mode control theory. Although, the stability and the performance is guaranteed by the proposed method, some design parameters have to be chosen by the designer manually. This problem can be solved by using genetic algorithms. The proposed method tunes the parameters of the controller, by which the reasonable accuracy and the control effort is achieved. The validity and the efficiency of the proposed method are verified through simulations.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.2
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• pp.195-200
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• 2004

Computer games use an intelligent method called flocking for boids' group behavioral modeling. Flocking can naturally model group behavioral patterns of unpredictable forms such as birds and fishes using some computer resource. In this paper, we implemented an ecosystem which is composed of predator and prey for group behavioral modeling of real underwater ecosystem. Also fuzzy logic is applied to implement instinct desire of ecosystem elements. As the result, we confirmed that the model can overcome breakdown of ecosystem and model naturally ecosystem behavior.

• Science of Emotion and Sensibility
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• v.7 no.2
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• pp.149-155
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• 2004

This research focus on analyzing the quality of clothing product in view of consumer's sensibility trend with a emphasis on measuring objective quality of pruduct. The fuzzy logic-based multi attribute model has been developed in order to evaluate the quality of clothing product. The overall quality of a clothing products can be divided into two distinct terms, product quality and brand value. Those two values are further analyzed with a relation to human sensibility.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.568-572
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• 1998

This paper defines Fuzzy Logic Units(FLUs) which are piece wise finite elements in multidimension Euclidean space, and redefines triangular membership functions which are different from those defined in traditional literature. By analyzing FLUs, this paper gives a constructive method of fuzzy rules in fuzzy logic systems based on finite element method. The simulation results of single machine to infinite bus system show the effectiveness of the proposed method in this paper.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.5 s.305
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• pp.13-18
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• 2005

Over the last few years, the control of bipedal robot has been considered a promising but difficult research field in the community of robotics. In this paper, a new robust output control method for a bipedal robot is proposed using the adaptive fuzzy logic. The adaptive fuzzy logic is used as an system approximator to cancel the unknown uncertainty. First, a model for a bipedal robot including switching leg influence, uncertainty and disturbance is presented. Second, a controller is designed in which the joint velocity measurement is not required. Fuzzy approximation error estimator is inserted in the system for tuning the fuzzy logic. Finally, the result of the computer simulation is presented to show the validity of the suggested control method.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1529-1532
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• 2007

Failure Mode, Effects, and Criticality Analysis (FMECA) is an extension of FMEA which includes a criticality analysis. The criticality analysis is used to chart the probability of failure modes against the severity of their consequences. The result highlights failure modes with relatively high probability and severity of consequences, allowing remedial effort to be directed where it will produce the greatest value. However, there are several limitations. Measuring severity of failure consequences is subjective and linguistic. Since The result of FMECA only gives qualitative and quantitative informations, it should be re-analysed to prioritize critical units. Fuzzy set theory has been introduced by Lotfi A. Zadeh (1965). It has extended the classical set theory dramatically. Based on fuzzy set theory, fuzzy logic has been developed employing human reasoning process. IF-THEN fuzzy rule based assessment approach can model the expert's decision logic appropriately. Fault tree analysis (FTA) is one of most common fault modeling techniques. It is widely used in many fields practically. In this paper, a simple fault tree analysis is proposed to measure the severity of components. Fuzzy rule based assessment method interprets linguistic variables for determination of critical unit priorities. An rail-way transforming system is analysed to describe the proposed method.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.18 no.10
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• pp.791-799
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• 2006

The fault diagnosis technologies may be applied in order to decrease the energy consumption and the maintenance cost of an air-conditioning system. In this paper, a fault diagnosis algorithm was developed by using a neural no-fault model and a dual fuzzy logic. Five different faults, such as the compressor valve leakage, the liquid line blockage, the condenser fouling, the evaporator fouling, and the refrigerant leakage of an air-conditioning system, were considered. The fault diagnosis algorithm was tested by using a fault simulation facility. Test results showed that the algorithm developed for this study was effective to detect and diagnose various faults. Therefore, this algorithm may be practically used for the fault diagnosis of an air-conditioning system.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.943-946
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• 2008

Many works have been done to enable computer, as brain of robot, to learn color categorization, most of them rely on modeling of human color perception and mathematical complexities. This paper aims at developing the innate ability of the computer to learn the human-like color categorization.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.2
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• pp.109-114
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• 2002

Various inverted pendulum systems have been frequently used as a model for the performance test of the proposed control system. We first identify a rotary-type inverted pendulum system by the Euler-Lagrange method and then design a FLC (Fuzzy Logic Controller) fur the plant. FLC`s are one of useful control schemes fur plants having difficulties in deriving mathematical models or having performance limitations with conventional linear control schemes. Many FLC`s imitate the concept of conventional PD (Proportional-Derivative) or PI (Proportional-Integral) controller. That is, the error e and the change-of-error are used as antecedent variables and the control input u the change of control input Au is used as its consequent variable for FLC`s. In this paper we design a simple-structured FLC for the rotary inverted pendulum system. We also perform some computer simulations to examine the tracking performance of the closed-loop system.