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Wind-speed prediction and analysis based on geological and distance variables using an artificial neural network: A case study in South Korea
- Koo, Junmo;
- Han, Gwon Deok;
- Choi, Hyung Jong;
- Shim, Joon Hyung
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WEB OF SCIENCE
33Citations
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42초록
In this study, we investigate the accuracy of wind-speed prediction at a designated target site using wind-speed data from reference stations that employ an ANN (artificial neural network). The reference and target sites fall into three geographical categories: plains, coast, and mountains of South Korea. Accurate wind-speed predictions are calculated by means of a correlation coefficient between the actual and simulated wind-speed data obtained by ANN. We investigate the effect of the geological characteristics of each category and the distance between reference and target sites on the accuracy of wind-speed prediction using ANN. (C) 2015 Elsevier Ltd. All rights reserved.
키워드
Wind energy; Artificial neural networks; Wind prediction; Climate data; ENERGY; MECHANISMS; PENINSULA; STATIONS; MODEL; POWER; AREA
- 제목
- Wind-speed prediction and analysis based on geological and distance variables using an artificial neural network: A case study in South Korea
- 저자
- Koo, Junmo; Han, Gwon Deok; Choi, Hyung Jong; Shim, Joon Hyung
- 발행일
- 2015-12-15
- 유형
- Article
- 저널명
- Energy
- 권
- 93
- 페이지
- 1296 ~ 1302
- 언어
- ENG
- 출판사
- PERGAMON-ELSEVIER SCIENCE LTD
- 발행국가
- 영국
- 분량
- 7 페이지
- ISSN
- E 1873-6785
P 0360-5442