[HTML][HTML] Interpretable machine learning for building energy management: A state-of-the-art review
Abstract Machine learning has been widely adopted for improving building energy efficiency
and flexibility in the past decade owing to the ever-increasing availability of massive building …
and flexibility in the past decade owing to the ever-increasing availability of massive building …
Explainable artificial intelligence (XAI) for intrusion detection and mitigation in intelligent connected vehicles: A review
The potential for an intelligent transportation system (ITS) has been made possible by the
growth of the Internet of things (IoT) and artificial intelligence (AI), resulting in the integration …
growth of the Internet of things (IoT) and artificial intelligence (AI), resulting in the integration …
Explainable AI for 6G use cases: Technical aspects and research challenges
Around 2020, 5G began its commercialization journey, and discussions about the next-
generation networks (such as 6G) emerged. Researchers predict that 6G networks will have …
generation networks (such as 6G) emerged. Researchers predict that 6G networks will have …
Applications of explainable AI for 6G: Technical aspects, use cases, and research challenges
When 5G began its commercialisation journey around 2020, the discussion on the vision of
6G also surfaced. Researchers expect 6G to have higher bandwidth, coverage, reliability …
6G also surfaced. Researchers expect 6G to have higher bandwidth, coverage, reliability …
Exploring local explanation of practical industrial AI applications: A systematic literature review
In recent years, numerous explainable artificial intelligence (XAI) use cases have been
developed, to solve numerous real problems in industrial applications while maintaining the …
developed, to solve numerous real problems in industrial applications while maintaining the …
Fault diagnosis using data fusion with ensemble deep learning technique in IIoT
Detecting the breakdown of industrial IoT devices is a major challenge. Despite these
challenges, real‐time sensor data from the industrial internet of things (IIoT) present several …
challenges, real‐time sensor data from the industrial internet of things (IIoT) present several …
[HTML][HTML] State-of-the-art review and synthesis: A requirement-based roadmap for standardized predictive maintenance automation using digital twin technologies
Recent digital advances have popularized predictive maintenance (PMx), offering enhanced
efficiency, automation, accuracy, cost savings, and independence in maintenance …
efficiency, automation, accuracy, cost savings, and independence in maintenance …
Deciphering optimal mixed-mode ventilation in the tropics using reinforcement learning with explainable artificial intelligence
The application of mixed-mode ventilation (MMV) in the tropics is challenging, given its hot
and humid climate. Consequently, there are limited periods when operating in natural …
and humid climate. Consequently, there are limited periods when operating in natural …
[HTML][HTML] Explainability and transparency of classifiers for air-handling unit faults using explainable artificial intelligence (XAI)
In recent years, explainable artificial intelligence (XAI) techniques have been developed to
improve the explainability, trust and transparency of machine learning models. This work …
improve the explainability, trust and transparency of machine learning models. This work …
Causal discovery-based external attention in neural networks for accurate and reliable fault detection and diagnosis of building energy systems
In the era of big data, data-driven models have become the most promising fault detection
and diagnosis solutions to building energy systems, due to their high accuracy and good …
and diagnosis solutions to building energy systems, due to their high accuracy and good …