Home ›
Entities
› academia
› Sensor fault diagnosis and correction for data center cooling system using hybrid multi-label random Forest and Bayesian Inference
Sensor fault diagnosis and correction for data center cooling system using hybrid multi-label random Forest and Bayesian Inference
Research article (Building and Environment, 2023) · cited 23× · AI/ML
Sensor fault diagnosis and correction for data center cooling system using hybrid multi-label random Forest and Bayesian Inference
Summary
Sensor fault diagnosis and correction for data center cooling system using hybrid multi-label random Forest and Bayesian Inference is a scholarly article[1].
Key Facts
Sensor fault diagnosis and correction for data center cooling system using hybrid multi-label random Forest and Bayesian Inference's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Sensor fault diagnosis and correction for data center cooling system using hybrid multi-label random Forest and Bayesian Inference. Retrieved May 24, 2026, from https://4ort.xyz/entity/sensor-fault-diagnosis-and-correction-for-data-center-cooling-system-using-hybrid-multi-label-random-forest-and-bayesian
MLA“Sensor fault diagnosis and correction for data center cooling system using hybrid multi-label random Forest and Bayesian Inference.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/sensor-fault-diagnosis-and-correction-for-data-center-cooling-system-using-hybrid-multi-label-random-forest-and-bayesian.
BibTeX@misc{4ortxyz_sensor-fault-diagnosis-and-correction-for-data-center-cooling-system-using-hybrid-multi-label-random-forest-and-bayesian_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Sensor fault diagnosis and correction for data center cooling system using hybrid multi-label random Forest and Bayesian Inference}}, year = {2026}, url = {https://4ort.xyz/entity/sensor-fault-diagnosis-and-correction-for-data-center-cooling-system-using-hybrid-multi-label-random-forest-and-bayesian}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Sensor fault diagnosis and correction for data center cooling system using hybrid multi-label random Forest and Bayesian Inference — https://4ort.xyz/entity/sensor-fault-diagnosis-and-correction-for-data-center-cooling-system-using-hybrid-multi-label-random-forest-and-bayesian (retrieved 2026-05-24)
