| 학회 | 한국화학공학회 |
| 학술대회 | 2007년 봄 (04/19 ~ 04/20, 울산 롯데호텔) |
| 권호 | 13권 1호, p.187 |
| 발표분야 | 공정시스템 |
| 제목 | The prediction of naphtha price using artificial neural networks |
| 초록 | Naphtha is one of the most important intermediate oil refining petrochemical product in petrochemical industry. Many petrochemicals such as ethylene, propylene, butadiene, benzene, and etc are produced by cracking process of naphtha. Therefore prices of these petrochemicals are dependant on their source, naphtha. Artificial neural networks are widely used data analysis and modeling techniques in computer science, combinatorial chemistry, medical science, and business fields. During the last few years, artificial neural networks have shown large potential for use in price prediction modeling in business area. In this study, artificial neural networks are applied to predict the price of naphtha with previous data. This proposed prediction suggests high accuracy and possibility on the modeling by artificial neural networks for managing petrochemical business. |
| 저자 | 이동헌, 박선원 |
| 소속 | 한국과학기술원 |
| 키워드 | artificial neural networks; network structures; business applications; prediction |
| 원문파일 | 초록 보기 |
