Pipeline Risk Assessment Using Artificial Intelligence: A Case from the Colombian Oil Network (Record no. 193608)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01771nab a2200205 4500 |
| 008 - CÓDIGOS DE INFORMACIÓN DE LONGITUD FIJA - INFORMACIÓN GENERAL | |
| Campo de control de longitud fija | 260224s2018 xxu ing |
| 041 ## - IDIOMA | |
| Idioma | Inglés |
| 245 00 - TITULO | |
| Título | Pipeline Risk Assessment Using Artificial Intelligence: A Case from the Colombian Oil Network |
| 260 ## - PUBLICACION, DISTRIBUCION, ETC | |
| Lugar de publicación, distribución, etc. | |
| Nombre de publicador, distribuidor, etc. | |
| Fecha de publicación, distribución, etc. | mar. 2018 |
| 270 ## - FECHA DE CARGA | |
| Fecha de carga | 09/10/2020 ; 09/10/2020 |
| 300 ## - DESCRIPCION FISICA | |
| Otra extensión | 7 p. ; 110-116 |
| 520 ## - RESUMEN, ETC | |
| Resumen | Currently, in order to make decisions regarding the safety of pipelines, the risk values and risk targets are becoming relevant points for discussion. However, the challenge is the reliability of the models employed to get the risk data. Such models usually involve a large number of variables and deal with high amounts of uncertainty. Therefore, there is a strong need for a powerful tool to cope with that uncertainty, and one of the best tools dealing with uncertainty is the implementation of artificial intelligence methods using fuzzy logic. Hence, this study aims to present an artificial intelligence inference system that minimizes the uncertainty of traditional approaches of risk assessment in pipelines. Also, in order to show the applicability of the model developed, this study presents a case from the Colombian oil transportation network. Besides that, this study presents an uncertainty analysis for the risk values, comparing the results of the inference system with traditional approach. The results show that the inference system performs better since the magnitude of the average error and its standard deviation are less than the traditional approach. |
| 581 ## - ESTADO DE COLECCIÓN | |
| Estado de colección | 1 |
| 773 0# - CORRECCIÓN | |
| Título | Process safety progress |
| Partes relacionadas | |
| 942 ## - DESC. DE MATERIAL | |
| Tipo de item KOHA | Artículo de Revista |
| 100 1# - RESPONSABLE PERSONAL | |
| Apellido, Nombre | Guzman Urbina, Alexander |
| 9 (RLIN) | 59767 |
| 100 1# - RESPONSABLE PERSONAL | |
| Apellido, Nombre | Aoyama, Atsushi |
| 9 (RLIN) | 59768 |
| Biblioteca propietaria | Biblioteca actual | Fecha de adquisición | Inventario | Total de préstamos | Inventario | Fecha de carga | Tipo de item KOHA |
|---|---|---|---|---|---|---|---|
| Biblioteca Alejandro Angel Bulgheroni | Biblioteca Alejandro Angel Bulgheroni | 06/03/2026 | 200065970 | 200065970 | 06/03/2026 | Artículo de Revista |
