@article{ART001602871},
author={서동혁 and 김규익 and KwangDeuk Kim and RYU KEUN HO},
title={Predicting Power Generation Patterns Using the Wind Power Data},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2011},
volume={16},
number={11},
pages={245-253}
TY - JOUR
AU - 서동혁
AU - 김규익
AU - KwangDeuk Kim
AU - RYU KEUN HO
TI - Predicting Power Generation Patterns Using the Wind Power Data
JO - Journal of The Korea Society of Computer and Information
PY - 2011
VL - 16
IS - 11
PB - The Korean Society Of Computer And Information
SP - 245
EP - 253
SN - 1598-849X
AB - Due to the imprudent spending of the fossil fuels, the environment was contaminated seriously and the exhaustion problems of the fossil fuels loomed large. Therefore people become taking a great interest in alternative energy resources which can solve problems of fossil fuels. The wind power energy is one of the most interested energy in the new and renewable energy. However, the plants of wind power energy and the traditional power plants should be balanced between the power generation and the power consumption. Therefore, we need analysis and prediction to generate power efficiently using wind energy. In this paper, we have performed a research to predict power generation patterns using the wind power data. Prediction approaches of datamining area can be used for building a prediction model. The research steps are as follows: 1) we performed preprocessing to handle the missing values and anomalous data. And we extracted the characteristic vector data. 2) The representative patterns were found by the MIA(Mean Index Adequacy) measure and the SOM(Self-Organizing Feature Map) clustering approach using the normalized dataset. We assigned the class labels to each data. 3) We built a new predicting model about the wind power generation with classification approach. In this experiment, we built a forecasting model to predict wind power generation patterns using the decision tree.
KW - New&Renewable Energy;Wind Power Energy;Self-Organizing Map;Predicting Patterns
DO -
UR -
ER -
서동혁, 김규익, KwangDeuk Kim and RYU KEUN HO. (2011). Predicting Power Generation Patterns Using the Wind Power Data. Journal of The Korea Society of Computer and Information, 16(11), 245-253.
서동혁, 김규익, KwangDeuk Kim and RYU KEUN HO. 2011, "Predicting Power Generation Patterns Using the Wind Power Data", Journal of The Korea Society of Computer and Information, vol.16, no.11 pp.245-253.
서동혁, 김규익, KwangDeuk Kim, RYU KEUN HO "Predicting Power Generation Patterns Using the Wind Power Data" Journal of The Korea Society of Computer and Information 16.11 pp.245-253 (2011) : 245.
서동혁, 김규익, KwangDeuk Kim, RYU KEUN HO. Predicting Power Generation Patterns Using the Wind Power Data. 2011; 16(11), 245-253.
서동혁, 김규익, KwangDeuk Kim and RYU KEUN HO. "Predicting Power Generation Patterns Using the Wind Power Data" Journal of The Korea Society of Computer and Information 16, no.11 (2011) : 245-253.
서동혁; 김규익; KwangDeuk Kim; RYU KEUN HO. Predicting Power Generation Patterns Using the Wind Power Data. Journal of The Korea Society of Computer and Information, 16(11), 245-253.
서동혁; 김규익; KwangDeuk Kim; RYU KEUN HO. Predicting Power Generation Patterns Using the Wind Power Data. Journal of The Korea Society of Computer and Information. 2011; 16(11) 245-253.
서동혁, 김규익, KwangDeuk Kim, RYU KEUN HO. Predicting Power Generation Patterns Using the Wind Power Data. 2011; 16(11), 245-253.
서동혁, 김규익, KwangDeuk Kim and RYU KEUN HO. "Predicting Power Generation Patterns Using the Wind Power Data" Journal of The Korea Society of Computer and Information 16, no.11 (2011) : 245-253.
