| contributor author | Park, Sangkyun | |
| contributor author | Kim, Juhyung | |
| contributor author | Kim, Jaejun | |
| contributor author | Wang, Seunghyeon | |
| date accessioned | 2026-08-20T21:24:57Z | |
| date available | 2026-08-20T21:24:57Z | |
| date copyright | 2025/06/13 | |
| date issued | 2025 | |
| identifier other | JCCEE5.CPENG-6677.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4314415 | |
| description abstract | AbstractFault detection and diagnosis (FDD) in air handling units (AHUs) is essential for
ensuring indoor air quality and prolonging system life span. However, the use of real
operational data for FDD has been limited in existing research, largely due to ...Practical ApplicationsThis study demonstrates how nine different machine-learning methods—ranging from traditional
approaches like naïve Bayes (NB) and decision trees (DT) to advanced models like artificial
neural networks (ANN) and Transformer-based ... | |
| publisher | American Society of Civil Engineers | |
| title | Fault Diagnosis of Air Handling Units in an Auditorium Using Real Operational Labeled Data across Different Operation Modes | |
| type | Journal Article | |
| journal volume | 39 | |
| journal issue | 5 | |
| journal title | Journal of Computing in Civil Engineering | |
| identifier doi | 10.1061/JCCEE5.CPENG-6677 | |
| journal fristpage | 04025065-1 | |
| journal lastpage | 04025065-18 | |
| page | 18 | |
| tree | Journal of Computing in Civil Engineering:;2025:;Volume ( 039 ):;issue: 005 | |
| contenttype | Fulltext | |