• Proceedings of the Safety Management and Science Conference
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• 2003.11a
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• pp.185-198
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• 2003

This study is to develop and operate the R-FCE(Real-time Fuzzy Control Expert System) model on the SBR(Sequency Batch Reactors) type sewage disposal facility which is for the environmental problem of future and the effective treatment. It is the system that regularly handles the input, output information in real time by the Fuzzy control IF-THEN rule. Nowadays the water pollution caused by the increase of population and the industrialization already exceeds the purifying ability of nature and is getting worse. The sewage disposal facility needs an expert having wide experience and know-how because the quality or quantity of inflow water is so irregular that the process of sewage disposal is difficult. In the nation, however, the accumulation of technology is so weak because field-operators avoid the long-term duty. So the accurate and speedy decision or control of field are difficult in the case of emergency situation.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.516-518
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• 1995

This paper presents the optimal short-term operation scheduling by using fuzzy linear programming method on cogeneration systems connected with auxiliary equipments. Simulation is performed in case of the bottomming cycle. Modeling of cogeneration systems and auxiliary equipments is done, the effectiveness of modeling is evaluated through the detailed simulation. After the optimal operation scheduling is established by using linear programming method, the last optimal operation scheduling is established by using fuzzy linear programming method. The results of simulation show the auxiliary equipments can be effeciently operated in case of the bottomming cycle by modeling proposed in this paper.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2380-2382
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• 2001

The objective of this paper is to design a force feedback controller for bilateral control of a master-slave manipulator system using fuzzy sliding mode control. In a bilateral control system the motion of the master device is followed by slave the one. While the force applied to the slave is reflected on the master. In this paper, a proposed controller applied to the system. Adding a switching control term to the input, robustness is improved. Also the knowledge of the system dynamics is not needed. The computer simulation results show the performance of the proposed fuzzy sliding mode controller.

• Smart Structures and Systems
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• v.14 no.2
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• pp.129-144
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• 2014

In this paper, a fuzzy inference system and an analytical hierarchy process-based online evaluation technique is developed to monitor the condition of the 32-km Donghai Bridge in Shanghai. The system has 478 sensors distributed along eight segments selected from the whole bridge. An online evaluation subsystem is realized, which uses raw data and extracted features or indices to give a set of hierarchically organized condition evaluations. The thresholds of each index were set to an initial value obtained from a structure damage and performance evolution analysis of the bridge. After one year of baseline monitoring, the initial threshold system was updated from the collected data. The results show that the techniques described are valid and reliable. The online method fulfills long-term infrastructure health monitoring requirements for the Donghai Bridge.

• Proceedings of the KIEE Conference
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• summer
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• pp.683-685
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• 2004

This paper introduces a basic design for the short-term load forecasting system using a commercial data base. The proposed system uses a hybrid load forecasting method using fuzzy linear regression for forecasting of weekends and Monday and general exponential smoothing for forecasting of weekdays. The temperature sensitive is used to improve the accuracy of the load forecasting during the summer season. MS-SQL Sever has been used a commercial data base for the proposed system and the database is operated by ADO(ActiveX Data Objects) and RDO(Remote Data Object). Database has been constructed by altering the historical load data for the past 38 years. The weather iDormation is included in the database. The developed short-term load forecasting system is developed as a user friendly system based on GUI(Graphical User interface) using MFC(Microsoft Foundation Class). Test results show that the developed system efficiently performs short-term load forecasting.

• Structural Monitoring and Maintenance
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• v.3 no.4
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• pp.315-333
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• 2016

This study aims to perform damage identification for Da-Sheng-Guan (DSG) high-speed railway truss arch bridge using fuzzy clustering analysis. Firstly, structural health monitoring (SHM) system is established for the DSG Bridge. Long-term field monitoring strain data in 8 different cases caused by high-speed trains are taken as classification reference for other unknown cases. And finite element model (FEM) of DSG Bridge is established to simulate damage cases of the bridge. Then, effectiveness of one fuzzy clustering analysis method named transitive closure method and FEM results are verified using the monitoring strain data. Three standardization methods at the first step of fuzzy clustering transitive closure method are compared: extreme difference method, maximum method and non-standard method. At last, the fuzzy clustering method is taken to identify damage with different degrees and different locations. The results show that: non-standard method is the best for the data with the same dimension at the first step of fuzzy clustering analysis. Clustering result is the best when 8 carriage and 16 carriage train in the same line are in a category. For DSG Bridge, the damage is identified when the strain mode change caused by damage is more significant than it caused by different carriages. The corresponding critical damage degree called damage threshold varies with damage location and reduces with the increase of damage locations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.7
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• pp.1387-1393
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• 2007

Even if the linearly separable patterns can be classified by the conventional single layer perceptron, the non-linear problems such as XOR can not be classified by it. A fuzzy single layer perceptron can solve the conventional XOR problems by applying fuzzy membership functions. However, in the fuzzy single layer perception, there are a couple disadvantages which are a decision boundary is sometimes vibrating and a convergence may be extremely lowered according to the scopes of the initial values and learning rates. In this paper, for these reasons, we proposed an enhanced fuzzy single layer perceptron algorithm that can prevent from vibration the decision boundary by introducing a bias term and can also reduce the learn time by applying the modified delta rule which include the learning rates and the momentum concept and applying the new linear activation function. Consequently, the simulation results of the XOR and pattern classification problems presented that the proposed method provided the shorter learning time and better convergence than the conventional fuzzy single layer perceptron.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.351-360
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• 2016

Rapid population growth with high living standards and high electronics use for personal comfort has raised the electricity demand exponentially. To fulfill this elevated demand, conventional energy sources are shifting towards low production cost and long term usable alternative energy sources. Hybrid renewable energy systems (HRES) are becoming popular as stand-alone power systems for providing electricity in remote areas due to advancement in renewable energy technologies and subsequent rise in prices of petroleum products. Wind and solar power are considered feasible replacement to fossil fuels as the prediction of the fuel shortage in the near future, forced all operators involved in energy production to explore this new and clean source of power. Presented paper proposes fuzzy logic based Energy Management System (EMS) for Wind Turbine (WT), Photo Voltaic (PV) and Diesel Generator (DG) hybrid micro-grid configuration. Battery backup system is introduced for worst environmental conditions or high load demands. Dump load along with dump load controller is implemented for over voltage and over speed protection. Fuzzy logic based supervisory control system performs the power flow control between different scenarios such as battery charging, battery backup, dump load activation and DG backup in most intellectual way.

• Journal of Korea Multimedia Society
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• v.18 no.2
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• pp.207-217
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• 2015

A multi-cup electric cupping system (MECS) was proposed, based on the ancient cupping method. MECS consisted of several cups that could be used simultaneously to treat 85 lumbago patients. Each cup was equipped with its own pump and pressure-monitoring system. The vacuum pressure of the cups was controlled using fuzzy logic. Through automated control of the vacuum pressure, long-term relief of muscle tightness was achieved. To develop a scientific foundation for this alternative treatment, we compared the Oswestry Disability Index (ODI) scores from conventional basic cupping to the ODI scores for our proposed MECS. The ODI scores using MECS decreased from $11.71{\pm}1.61$ before treatment to $4.81{\pm}1.48$ and $1.87{\pm}1.61$ after three and five treatments, respectively. The improvement rate in the ODI scores using MECS after three treatments was higher than that achieved by basic cupping. These results, combined with the convenience offered by enhanced information technology and fuzzy logic capabilities, should increase the efficiency of this device, and facilitate the opportunity to further explore the potential of Oriental medical practices.

• Journal of the Korea Safety Management & Science
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• v.13 no.3
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• pp.63-69
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• 2011

As environmental protection is becoming more and more important, green production has become a key issue for almost every manufacturer and will determine a manufacturer can be sustainable in the long term. Therefore a performance evaluation system for green suppliers is necessary to determine the suitability of suppliers to cooperate with the company. While the works on the evaluation and/or selection of suppliers are abundant, those that concern environmental issues are rather limited. The objective of this study is to construct a combined model based on fuzzy analytic hierarchy process (FAHP) and balanced scorecard (ESC) for evaluating green suppliers in the manufacturing industry. The ESC concept is applied to define the hierarchy with four major perspectives (i.e. financial, customer, internal business process, and learning and growth), and performance indicators are selected for each perspective. FAHP is then proposed in order to tolerate vagueness and ambiguity of information. Finally, FAHP is finally constructed to facilitate the solving process. With the proposed model, manufacturers can have a better understanding of the capabilities that a green supplier must possess and can evaluate and select the most suitable green supplier for cooperation.