• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.79-90
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• 2003

In this paper, we propose a multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments using multi-ultrasonic sensor. Instead of using “sensor fusion” method which generates the trajectory of a robot based upon the environment model and sensory data, “command fusion” method by fuzzy inference is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor using fuzzy inference is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we performed simulations in PC as well as experiments with IRL-2002. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.169-171
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• 1999

This paper presents a new demand control technique using fuzzy logic. Generally, predictive demand control method often brings about a large number of control actions and undesirable alarm during the beginning stage of the demand period. To solve this problem, a fuzzy predictive algorithm is proposed. The main idea of the method is the determination of sensitivity factor by using fuzzy logic. The performance of the proposed algorithm is tested through a case study.

• Journal of Construction Engineering and Project Management
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• v.7 no.3
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• pp.39-55
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• 2017

Preeminent performance of construction industry are unattainable with poor productivity resulting in time and cost over runs. Enhancement in productivity cannot be achieved without identifying and analyzing factors that adversely affect productivity. The objective therefore is to propose a productivity analysis model to quantify the probability of effect of factors influencing productivity by using fuzzy logic incorporated with relative importance index method, for various types of construction projects. To achieve this objective, a questionnaire survey was carried out targeting respondents of Indian construction industry, from four distinct projects, namely, residential, commercial, infrastructure and industrial projects. Based on questionnaire administered, the relative importance and ranks of factors demonstrated using relative importance index method. Probability assessment model to analyze productivity was then developed by using Fuzzy Logic Toolbox of MATLAB. The applicability of the proposed model was tested in seven construction projects and the probability of impact of factors on productivity evaluated. The results of application of model in the construction firms infers that the most contributing factor groups for most of the projects were discerned to be manpower, motivation and time group.

• Journal of Digital Convergence
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• v.15 no.9
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• pp.23-33
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• 2017

Given the expansion of globalization and international trade, the number of apparel consumers is growing every year, making it difficult to estimate the amount of handling needed from the logistics industry. To determine which management factors are important and which ones require improvement, fuzzy AHP was used. Using this method, the factors were ranked in the final analysis as follows: The first and most important factor was training employees (0.17), while the second was fire hazard management (0.169); the third-highest factor was inbound and outbound goods (0.142), and the fourth was the warehouse management system. Barcode management was ranked fifth. By these results, we were able to analyze the processes of clothing warehouses, noting that although the factors appear independent, they are actually connected while proceeding with full management control. Moreover, because of the special characteristics of garments, employee management is crucial. Due to the vulnerability of these goods to fire hazards, this factor must be well managed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.291-297
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• 2012

In this paper, potential field algorithm was used for path planning in dynamic environment. This algorithm is used to plan a robot path because of its elegant mathematical analysis and simplicity. However, there are some problems. The problems are problem of collision risk, problem of avoidance path, problem of time consumption. In order to solve these problems, we fused potential field with fuzzy system. The input of the fuzzy system is set using relative velocity and location of robot and obstacle. The output of the fuzzy system is set using the weighting factor of repulsive potential function. The potential field algorithm is improved by using fuzzy potential field algorithm and, path planning in various environment has been done.

• Structural Engineering and Mechanics
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• v.76 no.6
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• pp.781-797
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• 2020

In recent years, there is an increasing interest to optimize the fuzzy logic controller with different methods. This paper focuses on the optimization of a fuzzy logic controller applied to a seismically excited nonlinear building. In most cases, this problem is formulated based on the linear behavior of the structure, however in this paper, four sets of objective functions are considered with respect to the nonlinear responses of the structure as the peak interstory drift ratio, the peak level acceleration, the ductility factor and the maximum control force. The Improved Charged System Search is used to optimize the membership functions and the rule base of the fuzzy controller. The obtained results of the optimized and the non-optimized fuzzy controllers are compared to the uncontrolled responses of the structure. Also, the performance of the utilized method is compared with various classical and advanced optimization algorithms.

• The Journal of the Korea Contents Association
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• v.17 no.10
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• pp.231-240
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• 2017

Although the value of technology is evaluated by various methods, the result of technology valuation is different from evaluator and evaluation methods. Also the uncertainty on the result occurs with respect to the evaluation factors and evaluation model which should be considered. In the case of lack of data or comparison target, the credibility of the technology valuation result could be unsure. To decrease uncertainty of the technology valuation, Fuzzy concept and Fuzzy Comprehensive Evaluation method are applied instead of using existing methods which evaluate technology value(level) by the number. In the research, we firstly devide evaluation criteria into technology value factor and business value factor and evaluate the technology level for micro pressure wave reduction technology which has been developed in Korea. Technology value factor is marked as high level with 46%, and business value factor is very high with 44%, and the overall level of technology is evaluated between very high and high. It helps to compare to other technology in the rivalry by the factors as it can evaluate the value of technology by factors. The technology valuation method which is applied in this research is expected to use on analyzing technology level of new technology or alternative technology in many different field.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.86-91
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• 2004

As many organizations are searching for ways to compete more effectively in today's market environment. Image of Product is become the most important fact to improve their competition. The objectives of this paper are to provide an overview of PDM(Purchasing Decision Factor) and to discuss how to measure it more efficiently. This study develops a conceptual 'relation model of the purchasing decision factor', which identifies only performance based measurement, and proposes Fuzzy Measuring Method which uses the Fuzzy rule based algorithm to adept survey to date sets.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.329-334
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• 2007

This paper deals with self-tuning of fuzzy control systems. The fuzzy logic controller(FLC) has parameters that an: input and output scaling factors to effect control output. Tuning method is proposed for the scaling factor. In this paper. it is studied to control and to monitor the remote system statues using SOAP for communicate between the server part and the client part. The remote control system is controlled by using a web browser or a application program. The server part is waiting for the request of client part that uses internet network for communication each other and then the request is reached. the server part saves client data to the database and send a command set to the client part and then the client part sends command to controller in a cool chamber. The administrator can control and monitor the remote system just using a web browser. The effects of membership functions, defuzzification methods and scaling factors are investigated in the FLC system.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.990-992
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• 1996

The design of I/O scaling factors for fuzzy controller system is proposed in this paper. The proposed method is for nonlinear input scaling factor and variable output scaling factor. The fuzzy controller is evaluated by computer simulation on the 1st order process and 2nd order process. Simulation results showed robust characteristics for variable reference signal.