• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.114-118
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• 2012

The structure of layer for success factors of company project can be known by FSM which is available to recognize structure of the system. However, the relationship between the layers which belongs to the success factors of company projects can be unknown. From these viewpoints, this study is to analyze the structure of the relation between the layers contained the success factors of company projects using fuzzy system. Therefore, the relationship between lower vs middle layer and middle vs upper layer are obtained by evaluation model of company projects which has possibility and necessity of fuzzy system as fuzzy relation matrix. Using these results, fuzzy relation analysis is done and showed the usefulness.

• Structural Engineering and Mechanics
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• v.36 no.3
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• pp.381-399
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• 2010

A fuzzy hybrid control technique using a semi-active tuned mass damper (STMD) has been proposed in this study for mitigation of wind induced motion of a tall building. For numerical simulation, a third generation benchmark is employed for a wind-excited 76-story building. A magnetorheological (MR) damper is used to compose an STMD. The proposed control technique employs a hierarchical structure consisting of two lower-level semi-active controllers (sub-controllers) and a higher-level fuzzy hybrid controller. Skyhook and groundhook control algorithms are used as sub-controllers. When a wind load is applied to the benchmark building, each sub-controller provides different control commands for the STMD. These control commands are appropriately combined by the fuzzy hybrid controller during realtime control. Results from numerical simulations demonstrate that the proposed fuzzy hybrid control technique can effectively reduce the STMD motion as well as building responses compared to the conventional hybrid controller. In addition, it is shown that the control performance of the STMD is superior to that of the sample TMD and comparable to an active TMD, but with a significant reduction in power consumption.

• Journal of Advanced Navigation Technology
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• v.10 no.3
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• pp.219-225
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• 2006

This paper presents a method of object classification based on discrete wavelet transform (DWT) and fuzzy inference(FI). It concentrated not only on the design of fuzzy inference algorithm which is suitable for low speed uninhabited transportation such as, conveyor but also on the minimize the number of fuzzy rule. In the preprocess of feature extracting, feature parameters are extracted by using characteristics of the coefficients matrix of DWT. Such feature parameters as area, perimeter and a/p ratio are used obtained from DWT coefficients blocks. Secondly, fuzzy if - then rules that can be able to adapt the variety of surroundings are developed. In order to verify the performance of proposed scheme, In the middle of fuzzy inference, the Mamdani's and the Larsen 's implication operators are utilized. Experimental results showed that proposed scheme can be applied to the variety of surroundings.

• Journal of information and communication convergence engineering
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• v.19 no.4
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• pp.234-240
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• 2021

As the number of pet dog-related businesses is rising rapidly, there is an increasing need for reliable pet dog health information systems for casual pet owners, especially those caring for older dogs. Our goal is to implement a mobile pre-diagnosis system that can provide a first-hand pre-diagnosis and an appropriate coping strategy when the pet owner observes abnormal symptoms. Our previous attempt, which is based on the fuzzy C-means family in inference, performs well when only relevant symptoms are provided for the query, but this assumption is not realistic. Thus, in this paper, we propose a hybrid inference structure that combines fuzzy association memory and a double-layered fuzzy C-means algorithm to infer the probable disease with robustness, even when noisy symptoms are present in the query provided by the user. In the experiment, it is verified that our proposed system is more robust when noisy (irrelevant) input symptoms are provided and the inferred results (probable diseases) are more cohesive than those generated by the single-phase fuzzy C-means inference engine.

• Journal of Advanced Navigation Technology
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• v.12 no.4
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• pp.378-383
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• 2008

This paper presents a method of image analysis based on discrete cosine transform (DCT) and fuzzy inference(Fl). It concentrated not only on the design of fuzzy inference algorithm but also on incorporating human visual parameter(HVP) into transform coefficients. In the first, HVP such as entropy, texture degree are calculated from the coefficients matrix of DCT. Secondly, using these parameters, fuzzy input variables are generated. Mamdani's operator as well as ${\alpha}$-cut function are involved to simulate the proposed approach, and consequently, experimental results are presented to testify the performance and applicability of the proposed scheme.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.496-499
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• 2005

In this paper, We discuss various types of sublattice of the lattice of intuitionistic fuzzy subgroups of a given group. We Prove that a special class of intuitionistic fuf normal subgroups constitutes a modular sublattice of the lattice of intuitionistic fuzzy subgroups. Moreover, we exhibit the relationship of the sublattices of the lattice of intuitionistic fuzzy subgroups.

• Journal of Navigation and Port Research
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• v.31 no.8
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• pp.725-731
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• 2007

This paper aims to analyze an action about a port choice of shipper between two ports. For this propose, this paper analyzed a port choice action for Kwangyang and Busan port using a fuzzy logic and neural network. Also, this paper compared classification performance of fuzzy-neural network to Logit model, and analyzed a port choice action into change Para-meta such as freight volumes and service standard.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1723-1728
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• 2005

This article describes the fuzzy control of the 3-dimensional motion of the container cranes used in dockside container terminals. The container is suspended by four flexible cables via spreader, and due to the disturbances such as the wind and acceleration of cranes, the container undergoes translational(sway) and rotational position errors. And due to the uncertainty of weight and rotational inertia, accurate position control of container crane is difficult to realize. This paper, based on the analysis of 3-dimensional dynamics of container moving systems, describes the design of the fuzzy controller, which does not require the computation time to optimize the distribution of cable tension. The developed controller is shown effective in controlling the container position in the presence of gust and parameter uncertainties.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.429-438
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• 2007

Headache is one of the most common reasons for neurological consultation. Headache as many causes and symptoms. Therefore, screening method using questionaire is helpful in diagnosis of headache. This paper is to propose a medical diagnostic method to grasp patient's diseases using the relations between symptoms and diseases. For this purpose, we develop an interview chart assigned IF(intuitionistic fuzzy) grade with the relation among symptoms and three labels of headache. The method can be used to classify patient's tone of diseases with certain degrees of belief and its concerned symptoms.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.584-590
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• 2001

An inventory management system of manufacturing industry has a model of different kinds according to the objective and the situation. An inventory management system needs superior system technique in demand forecast, economical efficiency, reliability and application for stable supply of the finished goods, the raw materials and the parts. This paper proposes a demand forecast method based on fuzzy structured neural network, which uses min-operation and trapezoid membership function of fuzzy rules. So we can construct an intelligent inventory management system that make optimized decision-making for forecasting data with expert s opinion in fuzzy environment. The inventory management system uses intelligence agent and it could be adapted to a system environment change in order.