JICCE (한국정보통신학회)
Current Result Document :
| 한글제목(Korean Title) |
Chaotic Predictability for Time Series Forecasts of Maximum Electrical Power using the Lyapunov Exponent |
| 영문제목(English Title) |
Chaotic Predictability for Time Series Forecasts of Maximum Electrical Power using the Lyapunov Exponent |
| 저자(Author) |
Jae-Hyeon Park
Young-Il Kim
Yeon-Gyu Choo
|
| 원문수록처(Citation) |
VOL 09 NO. 04 PP. 0369 ~ 0374 (2011. 08) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
Generally the neural network and the Fuzzy compensative algorithms are applied to forecast the time series for power demand with the characteristics of a non-linear dynamic system, but, relatively, they have a few prediction errors. They also make long term forecasts difficult because of sensitivity to the initial conditions.
In this paper, we evaluate the chaotic characteristic of electrical power demand with qualitative and quantitative analysis methods and perform a forecast simulation of electrical power demand in regular sequence, attractor reconstruction and a time series forecast for multi dimension using Lyapunov Exponent (L.E.) quantitatively. We compare simulated results with previous methods and verify that the present method is more practical and effective than the previous methods. We also obtain the hourly predictability of time series for power demand using the L.E. and evaluate its accuracy. |
| 키워드(Keyword) |
Chaos
Lyapunov Exponent
Electrical Power
Forecast
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| 파일첨부 |
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