• New & Renewable Energy
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• v.2 no.2 s.6
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• pp.37-43
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• 2006

In this paper, the first forecasting system of wind power generation, KIER Forecaster is presented. KIER Forecaster has been constructed based on statistical models and was trained with wind speed data observed at Gosan Weather Station nearby Walryong Site. Due to short period of measurements at Walryong Site for training the model, Gosan wind data were substituted and transplanted to Walryong Site by using Measure-Correlate-Predict(MCP) technique. The results of One to Three-hour advanced forecasting models are consistent with the measurement at Walryong site. In particular, the multiple regression model by classification of wind speed pattern, which has been developed in this work, shows the best performance comparing with neural network and auto-regressive models.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.5
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• pp.549-556
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• 2009

One of the basic technology for implementing the autonomy of UGV(Unmanned Ground Vehicle) is a path planning algorithm using obstacle and raw terrain information which are gathered from perception sensors such as stereo camera and laser scanner. In this paper, we propose a generation method of DVGM(Directional Velocity Grid Map) which have traverse speed of UGV for the five heading directions except the rear one. The fuzzy system is designed to generate a resonable traveling speed for DVGM from current patch to the next one by using terrain slope, roughness and obstacle information extracted from raw world model data. A simulation is conducted with world model data sampled from real terrain so as to verify the performance of proposed fuzzy inference system.

• Journal of Korea Multimedia Society
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• v.5 no.2
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• pp.206-214
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• 2002

In this paper, it is designed and verified the baseband system that performs various protocol functions of specification of the Bluetooth system. In order to verify the developed circuits, various baseband functions are tested by using the ModelSim simulator. The developed circuits operate at 4MHz main clock. Test suite includes hap selection function, generation of the sync word, error correction(1/3 rate FEC, 2/3 rate FEC), HEC generation/checking, CRC generation/checking, data whitening/dewhitening and packet trans/reception procedure. etc. As a result of the simulation, it is verified that the developed baseband system conform to the specification of the Bluetooth system.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.24-27
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• 2003

High-resolution satellite images at sub-5m footprint are becoming increasingly available to the earth observation community and their respective clients. The related cameras are all using linear array CCD technology for image sensing. The possibility and need for accurate 3D object reconstruction requires a sophisticated camera model, being able to deal with such sensor geometry. We have recently developed a full suite of new methods and software for the precision processing of this kind of data. The software can accommodate images from IKONOS, QuickBird, ALOS PRISM, SPOT5 HRS and sensors of similar type to be expected in the future. We will report about the status of the software, the functionality and some new algorithmic approaches in support of the processing concept. The functionality will be verified by results from various pilot projects. We put particular emphasis on the automatic generation of DSMs, which can be done at sub-pixel accuracy and on the semi-automated generation of city models.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.822-829
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• 2022

According to existing study into the remote fault diagnosis procedure, the current diagnostic approach has an imperfect decision model, which only supports communication in a close distance. An Internet of Things (IoT)-based remote fault diagnostic approach for wind power equipment is created to address this issue and expand the communication distance of fault diagnosis. Specifically, a decision model for active power coordination is built with the mechanical energy storage of power generation equipment with a remote diagnosis mode set by decision tree algorithms. These models help calculate the failure frequency of bearings in power generation equipment, summarize the characteristics of failure types and detect the operation status of wind power equipment through IoT. In addition, they can also generate the point inspection data and evaluate the equipment status. The findings demonstrate that the average communication distances of the designed remote diagnosis method and the other two remote diagnosis methods are 587.46 m, 435.61 m, and 454.32 m, respectively, indicating its application value.

• Smart Media Journal
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• v.13 no.2
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• pp.9-15
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• 2024

In this paper, a Diffusion Multi-step Classifier (DMC) is proposed to address the imbalance issue in credit prediction. DMC utilizes a Diffusion Model to generate continuous numerical data from credit prediction data and creates categorical data through a Multi-step Classifier. Compared to other algorithms generating synthetic data, DMC produces data with a distribution more similar to real data. Using DMC, data that closely resemble actual data can be generated, outperforming other algorithms for data generation. When experiments were conducted using the generated data, the probability of predicting delinquencies increased by over 20%, and overall predictive accuracy improved by approximately 4%. These research findings are anticipated to significantly contribute to reducing delinquency rates and increasing profits when applied in actual financial institutions.

• Journal of IKEEE
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• v.27 no.3
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• pp.280-287
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• 2023

Deep learning advancements can solve computer vision problems, but large-scale datasets are necessary for high accuracy. In this paper, we propose an image generation technique using object bounding boxes and image edge components. The object bounding boxes are extracted from the images through object detection, and image edge components are used as input values for the image generation model to create new image data. As results of experiments, the images generated by the proposed method demonstrated similar image quality to the source images in the image quality assessment, and also exhibited good performance during the deep learning training process.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.3
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• pp.164-168
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• 2015

Due to the uncertainty of weather, it is difficult to construct an accurate forecasting model for daily PV power generation. It is very important work to know PV power in next day to manage power system. In this paper, correlation analysis between weather and power generation was carried out and daily PV power forecasting models based on Extreme Learning Machine(ELM) was presented. Performance of district ELM model was compared with single ELM model. The proposed method has been tested using actual data set measured in 2014.

• Journal of Industrial Technology
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• v.20 no.A
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• pp.131-138
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• 2000

A past monthly data is not faithful so much for a short term. But, the stochastic generation technique was provide of a long-term data. Thus this study is used a data which generated a monthly inflow amounts data by Thomas-Fiering model. This model is needed a certain process which determination of distribution, decision of continuous durability, etc. It was generated a inflow data every one month as Thomas-Fiering method. The generated inflow data was used input data for a monthly cumulative analysis. This analysis obtained a storage capacities which would be required during droughts having various return periods. It was presented a equation of fitting regression that was carried out regression analysis of 5, 10, 20, 50 years period.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.3
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• pp.107-116
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• 2005

The paper addresses modeling and analysis of a grid-connected photovoltaic generation system (PV system). PSCAD/EMTDC, an industry standard simulation tool for studying the transient behavior of electric power system and apparatus, is used to conduct all aspects of model implementation and to carry out extensive simulation study. This paper is aimed at sharing with the PSCAD/EMTDC user community our user-defined model for PV system applications, which is not yet available as a standard model within PSCAD/EMTDC. An equivalent circuit model of a solar cell has been used for modeling solar array. A series of parameters required for array modeling have been estimated from general specification data of a solar module. A PWM voltage source inverter (VSI) and its current control scheme have been implemented. A maximum power point tracking (MPPT) technique is employed for drawing the maximum available energy from the PV array. Comprehensive simulation results are presented to examine PV array behaviors and PV system control performance in response to irradiation changes. In addition, dynamic responses of PV array and system to network fault conditions are simulated and analysed.