Name
Title | ||
|---|---|---|
Deep understanding in industrial processes by complementing human expertise with interpretable patterns of machine learning. |
Abstract | ||
|---|---|---|
•The paper combines domain knowledge (DK) with machine learning (ML).•Patterns of logical analysis of data (LAD) are used by experts to enrich the DK.•The LAD patterns identify fault causes that are not represented in the DK.•The identified causes are used to enrich the fault trees in industrial plants. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.eswa.2019.01.011 | Expert Systems with Applications |
Keywords | Field | DocType |
Fault detection and diagnosis (FDD),Logical analysis of data (LAD),Fault tree analysis (FTA),Machine learning and pattern recognition,Causality analysis | Process industry,Data mining,Causality,Domain knowledge,Fault detection and isolation,Computer science,Logical analysis of data,Artificial intelligence,Unexpected events,Fault tree analysis,Machine learning | Journal |
Volume | ISSN | Citations |
122 | 0957-4174 | 2 |
PageRank | References | Authors |
0.36 | 40 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ahmed Ragab | 1 | 30 | 3.93 |
| Mohamed El-Koujok | 2 | 9 | 1.47 |
| Hakim Ghezzaz | 3 | 2 | 0.36 |
| Mouloud Amazouz | 4 | 10 | 1.61 |
| Mohamed-Salah Ouali | 5 | 63 | 5.75 |
| Soumaya Yacout | 6 | 133 | 13.08 |