| 학회 |
한국화학공학회 |
| 학술대회 |
2015년 봄 (04/22 ~ 04/24, 제주 ICC) |
| 권호 |
21권 1호, p.190 |
| 발표분야 |
공정시스템 |
| 제목 |
An Error Correction Strategy for forecasting Renewable Energy Output |
| 초록 |
Forecasting is very powerful but challenging task for operating complex real world problems. A reliable forecasting strategy thus allows us to reduce significant amount of costs. However simply adding more information in the forecasting model does not guarantee the increased performance of the system. A systematic modeling approach would be desirable for the specific problem case. The issue is then how to develop an elaborate forecasting modeling framework. Neural network has proven to be a very powerful tool in forecasting many practical problems. Its modeling procedure is complicated and in need of many delicate jobs after adjustment. In this paper multiple neural network models are compared to develop a well-tuned with a special focus on renewable energy system. |
| 저자 |
류준형1, 이수빈2, 이인범2
|
| 소속 |
1동국대, 2포스텍 |
| 키워드 |
forecasting; error correction
|
| E-Mail |
|
| 원문파일 |
초록 보기 |
