
doi: 10.55274/r0012192
The PRCI Technical Committees have completed multiple research projects that used artificial intelligence techniques; this is a summary of that work. Since not all studies sponsored by other industry groups (e.g., API, EPRG, APIA, etc.) or by individual pipelines companies are not included, this report does not represent a review of the topic in the broader industry-wide sense. Instead, it is designed to provide a guide to past work so that current PRCI members and its research contractors can identify and locate project reports that might be in the demonstration of the use of using artificial intelligence methods to support the enhancement of the safe, efficient, and reliable operation of pipeline systems.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
