• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.277-280
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• 2006

Most real world design evaluation and risk-based decision support combine quantitative and qualitative (linguistic) variables. Decision-making based on conventional mathematics that combines qualitative and quantitative concepts always exhibit difficulty in modelling actual problems. The successful selection process for choosing a design/procurement proposal is based on a high degree of technical integrity, safety levels and low costs in construction, corrective measures, maintenance, operation, inspection and preventive measures. However, the objectives of maximising the degree of technical performance, maximising the safety levels and minimising the costs incurred are usually in conflict, and the evaluation of the technical performance, safety and costs is always associated with uncertainties, especially for a novel system at the initial concept design stage. In this paper, a design-decision support framework using a composite structure methodology grounded in approximate reasoning approach and evidential reasoning method is suggested for design evaluation of machinery space of a ship engine room at the initial stages. It is a Multiple Attribute Decision-Making (MADM) or Multiple Criteria Decision Making (MCDM) framework, which provides a juxtaposition of cost, safety and technical performance of a system during evaluation to assist decision makers in selecting the winning design/procurement proposal that best satisfies the requirement in hand. An illustrative example is used to demonstrate the application of the proposed framework.

• Journal of Korea Multimedia Society
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• v.9 no.9
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• pp.1095-1106
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• 2006

Recently, many effort is demanded for appropriate operation and management of the Electronic commerce system. Electronic commerce system must provide information satisfying customers. To do this, many kinds of studies are being advanced about electronic commerce system using intelligent agent technology. In this paper, We propose a support system for goods based on Case-Based Reasoning(CBR) and multi-crossselling technology. The system can supply the information of goods that is suitable about customer need under specification condition with CBR technique and can search several goods approximate to customer pattern using Multi-crossselling technique.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.532-538
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• 1998

In this paper, a new adaptive fuzzy inference method using neural network based fuzzy reasoning is proposed to make a fuzzy logic control system more adaptive and more effective. In most cases, the design of a fuzzy inference system rely on the method in which an expert or a skilled human operator would operate in that special domain. However, if he has not expert knowledge for any nonlinear environment, it is difficult to control in order to optimize. Thus, using the proposed adaptive structure for the fuzzy reasoning system can controled more adaptive and more effective in nonlinear environment for changing input membership functions and output membership functions. The proposed fuzzy inference algorithm is called adaptive neuro-fuzzy control(ANFC). ANFC can adapt a proper membership function for nonlinear plant, based upon a minimum number of rules and an initial approximate membership function. Nonlinear function approximation and rotary inverted pendulum control system ar employed to demonstrate the viability of the proposed ANFC.

• Journal of the Korean Institute of Intelligent Systems
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• v.3 no.2
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• pp.3-17
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• 1993

The fuzzy pattern matching technique has been developed in the framework of fuzzy set and possibility theory in order to take into account the imprecision and the uncertainty pervading values which have to be compared to requirements (which may be fuzzy) in a pattern matching process. This paper restates the basic principles and extends them to situations where (sub)patterns are only required to be satisfied up to a given tolerance (which may be fuzzy), or where the different subparts of a compound pattern may have various levels of importance. Both cases correspond to a weakening of elementary patterns. which can be expressed by a fuzzy relations modelling an approximate equality or an uncertain strict equality respectively. We also study the more sophisticated case where some elementary patterns have not to be satisfied with the highest priority provided that weaker requirements remain satisfied. The fuzzy pattern matching technique applies in a variety of problems including the evaluation of soft queries with respect to a fuzzy database, the evaluation of the fuzzy condition parts of rules in approximate reasoning, or the evaluation of the belonging of an ill-known object to a flexible class in classification problems.

• Korean Journal of Construction Engineering and Management
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• v.14 no.3
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• pp.42-52
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• 2013

The aim of this study is to present a prediction model of construction cost for a bridge that has a high reliability using historical data from the planning phase based on a CBR (Case-Based Reasoning) method in order to overcome limitations of existing construction cost prediction methods, which is linearly estimated. To do this, a reasoning model of bridge construction cost by a spreadsheet template was suggested using complexly both CBR and GA (Genetic Algorithm). Besides, this study performed a case study to verify the suggested cost reasoning model for bridge construction projects. Measuring efficiency for a result of the case study was 8.69% on average. Since accuracy of the suggested prediction cost is relatively high compared to the other analysis methods for a prediction of construction cost, reliability of the suggested model was secured. In the case that information for detailed specifications of each bridge type in an initial design phase is difficult to be collected, the suggested model is able to predict the bridge construction cost within the minimized measuring efficiency with only the representative specifications for bridges as an improved correction method. Therefore, it is expected that the model will be used to estimate a reasonable construction cost for a bridge project.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.237-240
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• 2001

An image processing and decision making method for the Automatic Surveillance System is proposed. The aim of our Automatic Surveillance System is to detect a moving object and make a decision on whether it is human or not. Various object features such as the ratio of the width and the length of the moving object, the distance dispersion between the principal axis and the object contour, the eigenvectors, the symmetric axes, and the areas if the segmented region are used in this paper. These features are not the unique and decisive characteristics for representing human Also, due to the outdoor image property, the object feature information is unavoidably vague and inaccurate. In order to make an efficient decision from the information, we use a fuzzy rules base system ai an approximate reasoning method. The fuzzy rules, combining various object features, are able to describe the conditions for making an intelligent decision. The fuzzy rule base system is initially constructed by heuristic approach and then, trained and tasted with input/output data Experimental result are shown, demonstrating the validity of our system.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.486-495
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• 2001

This paper describes an implementation of the interval based expert system for syndrome differential diagnosis of Oriental Traditional Medicine (OTM). An approximate reasoning model using fuzzy logic for syndrome differential diagnosis is proposed. Based on this model, we implemented the system for diagnosing Eight rule diagnosis, organ diagnosis and then final differential syndrome of OTM. After carrying out inference process, the system will provide patient\`s syndromes differentiation diagnosis in the intervals and will give the explanation, which helps the user to understand the obtained conclusions.

• Proceedings of the KIPE Conference
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• 2008.06a
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• pp.127-129
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• 2008

This paper describes a method of approximate reasoning for fuzzy control of servo system, based on decomposition of -level fuzzy sets. It is propose that logic circuits for fuzzy PI+PD are a body from fuzzy inference to defuzzificaion in cases where the output variable u directly is generated PWM. The effectiveness for robust and faster response of the fuzzy control scheme is verified for a variable parameter by comparison with a PID control and fuzzy control. A position control of DC servo system with a fuzzy logic controller successfully demonstrated.

• International Journal of Control, Automation, and Systems
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• v.4 no.1
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• pp.17-29
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• 2006

A novel inverse kinematics solution based on the back propagation neural network (NN) for redundant manipulators is developed for online obstacles avoidance. A laser transducer at the end-effctor is used for online planning the trajectory. Since the inverse kinematics in the present problem has infinite number of joint angle vectors, a fuzzy reasoning system is designed to generate an approximate value for that vector. This vector is fed into the NN as a hint input vector rather than as a training vector to guide the output of the NN. Simulations are implemented on both three- and four-link redundant planar manipulators to show the effectiveness of the proposed position control system.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.627-629
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• 1999

This paper presents a new FDI scheme based on dynamic fuzzy model(DFM) for the nonlinear system. The dynamic behavior of a nonlinear system is represented by a set of local linear models. The parameters of the DFM are identified in on-line and aggregated to generate a residual vector by the approximate reasoning. The neural network classifer learns the relationship between the residual vector and fault type and used both for the detection and isolation of process faults We apply the proposed FDI scheme to the FDI system design for a two-tank system and show the usefulness of the proposed scheme.