• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.118-121
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• 2003

Generally, the repeater in CDMA(Code Division Multiple Access) included HPA(HI-Power Amplifier) to amplifier communication signals. Also , HPA contained PD(Predistortor) to maintain the linearization of amplifier characteristics. A configuration component of PD have been used electricity nonlinear devices such that diode. But this diode takes many influences at the circumstance temperature. Consequently, it can't maintain output linearization, and drop the communication quality. The manufacturer set bias of the circuit to the manual at the first out of ware-house low But the Q-point changes according to the change of the high temperature or low temperature. Therefore, we designed a system to maintain the Q-point by FDM(Fuzzy Decision Maker) in this paper.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.4
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• pp.247-253
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• 2011

A sustainability of electricity supply has emerged as a critical issue for low carbon green growth in South Korea. Wind power is the fastest growing source of renewable energy. However, due to its own intermittency and volatility, the power supply generated from wind energy has variability in nature. Hence, accurate forecasting of wind speed and power plays a key role in the effective harvesting of wind energy and the integration of wind power into the current electric power grid. This paper presents a short-term wind speed prediction method based on support vector regression. Moreover, particle swarm optimization is adopted to find an optimum setting of hyper-parameters in support vector regression. An illustration is given by real-world data and the effect of model regularization by particle swarm optimization is discussed as well.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.18-23
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• 2008

A FCM with locational price and regional information between locations are proposed in this paper. Any point in a networked system has its own values indicating the physical characteristics of that networked system and regional information at the same time. The similarity measure used for FCM in this paper is defined through the system-wide characteristic values at each point. To avoid the grouping of geometrically distant locations with similar measures, the locational information are properly considered and incorporated in the proposed similarity measure. We have verified that the proposed measure has produced proper classification of a networked system, followed by an example of a networked electricity system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.283-286
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• 2003

Generally, the repeater in CDMA(Code Division Multiple Access) included HPA(HI-Power Amplifier) to amplifier communication signals. Also, HPA contained PD(Predistortor) to maintain the linearization of amplifier characteristics A configuration component of PD have been used electricity nonlinear devices such that diode. But this diode takes many influences at the circumstance temperature. Consequently, st can't maintain output linearization, and drop the communication Duality. The manufacturer set bias of the circuit to the manual at the first out of ware-house low. But the Q-point changes according to the change of the high temperature or low temperature. Therefore, we designed a system to maintain the Q-point by FDM(Fuzzy Decision Maker) in this paper.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.61-66
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• 1998

Since a gas turbine is made use of generating electricity for peak time, it is a very important to operate a peak time load with safety. The main components of a gas turbine are the compressor, the combustion chamber and the turbine. So, there also must be modeled a component of gas turbines for the control with safety but it is not easy. In this paper we acquire a transfer function based on the operations data of Gun-san gas turbine and study to apply Neural-Network 2-DOF PID controler to control loop of gas turbine to reduce phenomena caused by integral and derivative actions through simulation. We obtained satisfactory results to disturbances of subcontrol loop such as, fuel flow, air flow, turbine extraction temperature.

• Journal of Integrative Natural Science
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• v.9 no.3
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• pp.199-205
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• 2016

In this paper, we established ZIGBEE home network and combined smart-grid and u-Healthcare system. We assisted for amount of electricity management of household by interlocking home devices of wireless sensor, PLC modem, DCU and realized smart grid and u-Healthcare at the same time by verifying body heat, pulse, blood pressure change and proceeded living body signal by using SVM algorithm and variety of ZIGBEE network channel and enabled it to check real-time through IHD which is developed by user interface. In addition, we minimized the rate of energy consumption of each sensor node when living body signal is processed and realized Query Processor which is able to optimize accuracy and speed of query. We were able to check the result that is accuracy of classification 0.848 which is less accounting for average 17.9% of storage more than the real input data by using Mjoin, multiple query process and SVM algorithm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.108-112
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• 2012

A sustainable production of electricity is essential for low carbon green growth in South Korea. The generation of wind power as renewable energy has been rapidly growing around the world. Undoubtedly wind energy is unlimited in potential. However, due to its own intermittency and volatility, there are difficulties in the effective harvesting of wind energy and the integration of wind power into the current electric power grid. To cope with this, many works have been done for wind speed and power forecasting. It is reported that, compared with physical persistent models, statistical techniques and computational methods are more useful for short-term forecasting of wind power. Among them, support vector regression (SVR) has much attention in the literature. This paper proposes an SVR based wind speed forecasting. To improve the forecasting accuracy, a fuzzy clustering is adopted in the process of SVR modeling. An illustrative example is also given by using real-world wind farm dataset. According to the experimental results, it is shown that the proposed method provides better forecasts of wind power.

• Journal of the Korean Solar Energy Society
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• v.25 no.1
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• pp.1-10
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• 2005

In this paper, 150W photovoltaic system using neural network tracker is proposed, the system designed as the normal line of the solar cell always runs parallel the ray of the sun. This design can minimize the cosine loss of the system output results of solar cell are sensitive to the change of weather and insolation condition don't react rapidly to parameter condition change such as system circumstance and deterioration. To achieve precise operation of photovoltaic tracker system using method of intelligent control, Neural Network is used in the design of the photovoltaic tracker system drive. The control performance of this system drive influenced by the environment parameter such as weather condition and motor parameter variations. we used synchronous motor in this tracker and the experimental results show that the fixing system shows 10,159[Wh] and tracking system shows 12,360[Wh] electricity.

• Current Photovoltaic Research
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• v.10 no.4
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• pp.133-137
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• 2022

The economic feasibility of a photovoltaic (PV) system is greatly influenced by the initial investment cost for system installation. Also, electricity generation by PV system is highly important. The profits competitiveness of PV system will be maximized through intelligent operation and maintenance (O&M). Here, we developed a microconverter which can maximize electricity generation from PV modules by tracking the maximum power point of PV modules, and help efficient O&M. Also, the microconverter mitigates current mismatch caused by shading, hence maximize power generation. The microconverters were installed PV modules and demonstrated through the field tests. Power outputs such as voltage, string current were measured with variuos weather environments and partial shadings. We found that PV modules with the microconvertors shows 12.05% higher power generation compared to the reference PV modules.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.546-549
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• 2022

The installation rate of AMI (advanced metering infrastructure) capable of automatic electricity measurement is less than 43% nationwide and 10.5% in rural areas, which is very poor. Therefore, for the smart grid, automatic information recording of the watt-hour meter is required. For this purpose, it is necessary to develop a system capable of remote meter reading and use control by improving the existing watt-hour meter. In this paper, in order to enable the AMI function of the existing electricity meter, the remote meter reading and control technology of the existing electricity meter for AMI, the core of the smart grid, was developed using IoT and AI. The main research content was to recognize numbers using Tensorflow and Open-cv to convert it into a power meter sensing device for SG. We confirmed and checked the performance using the protyope system.