In current studies of the belief rule base (BRB) model, attributes are assumed to be fully reliable and observation data directly used as input. However, in engineering practice, may affected by some disturbance factors, including quality sensors noise environment. Then, reliability modeling accuracy BRB is therefore influenced. As such, a new model with attribute (BRB-r) proposed this paper. particular, calculation method given based on statistical method. Moreover, integrate into BRB-r,...

Safety assessment is one of important aspects in health management. In safety for practical systems, three problems exist: lack observation information, high system complexity and environment interference. Belief rule base with attribute reliability (BRB-r) an expert that provides a useful way dealing these problems. BRB-r, once the input information unreliable, belief influenced, which further influences accuracy its output degree. On other hand, when many characteristics exist, combination...

This paper develops a new trustworthy fault diagnosis (TFD) method based on belief rule base expert system with combining multi-source uncertainty information for vehicle, such as flying machine. To improve the performance of (BRB-MU) is developed, where influence random environment disturbance addressed by introducing uncertain factors input characteristics. In BRB-MU, characteristics are calculated signal to noise ratio method. The developed BRB-MU model aims handle three problems:...

In the technology of wireless sensor network (WSN), fault diagnosis based on fusion data analysis has attracted attention in field. It can detect and correct faults nodes time to improve accuracy fusion. this paper, characteristics WSN are analyzed, a method is proposed for belief rule base (BRB) model. First, process described WSN. Then, sensors analyzed from aspects time, space, attributes. Finally, model hierarchical BRB To make results more accurate, covariance matrix adaptation...

As sensors readings are used for vehicle flight control, their reliability directly affects the performance. This paper develops a new fault diagnosis and tolerance method sensor failures of vehicles by addressing three problems:unavailable faulty data, difficulty in establishing analytical system, inconsistence expert cognitive ability. For purpose, belief rule base model with multi-expert joint (BRB-ME) is proposed. The first two problems handled combining small size observation data...

Abstract Due to the harsh operating environment and ultralong hours of wireless sensor networks (WSNs), node failures are inevitable. Ensuring reliability data collected by WSN necessitates utmost importance diagnosing faults in nodes within WSN. Typically, initial step fault diagnosis involves extracting numerical features from neighboring nodes. A solitary feature is often assigned a high weight, resulting failure effectively distinguish between all types faults. Therefore, this study...

An effective fault detection strategy has always been the focus of smart grid system research. Fast and accurate is basis for complex systems to maintain reliability security. However, traditional methods often ignore interpretability model while pursuing high accuracy. Complex models can usually provide higher accuracy, but lack transparency interpretability, making it difficult operators understand trust results model. Therefore, a new based on an adaptive interpretable belief rule base...

This article provides a detailed examination of the principles and applications radar technology within autonomous driving systems, with particular focus on its integration into Advanced Driver Assistance Systems (ADAS). It highlights essential roles sensors in critical technologies including Adaptive Cruise Control (ACC), Blind Spot Monitoring (BSM), Automatic Emergency Braking (AEB), Automated Parking (APA). The discussion extends to address challenges opportunities associated improving...

With excellent interpretability, the fuzzy rule-based method stands as a formidable instrument for knowledge representation and learning. Nowadays, problem with multidimensional input information is widespread, leading to large rule base making it difficult embed expert knowledge. In addition, human not entirely reliable, causing inaccurate reasoning results. this article, novel large-scale linguistic Z-number belief (LSLZ-BRB) proposed above unreliable Specifically, mapping under...

With the growing demand for high safety in industrial system, fault diagnosis has attracted more and attention. Currently, belief rule base (BRB) shown an excellent performance modeling complex where expert knowledge is used effectively. Existing BRB models are assumed that inputs of attributes independent attribute correlation not taken into account. However, some engineering there obvious among these attributes. The correlated may produce redundant information which limits abilities to...