Work

A Bayesian Network-Based Prediction Method for Continuous Operational Capability During Team Collaborative Tasks

Year: 2025

Type: article

Abstract: In the context of team collaborative tasks, continuous operational capability represents a crucial indicator of operational efficiency and a pivotal area of current research. A reduction in the continuous operational capability of team members will inevitably result in an increase in the error rate, which will prevent the completion of the task. In certain circumstances, this may even result in more severe consequences. To guarantee that team members possess optimal operational capabilities, it is imperative to conduct research on continuous operational capability prediction. This paper presents a Bayesian network-based continuous operational capability prediction model for team collaborative tasks. The model is developed based on the causal relationship of the continuous operational capability evolution, and through the improvement on the Bayesian network so that it can be suitable for individual personnel. The experimental verification demonstrates that the model produces accurate results and can be employed to predict the continuous operational capability and its changing trend.

Source: Mathematics

DOI: 10.3390/math13193117

Authors: Shanran Wang, Liping Pang, Pei Li, Tingting Jiao, Xiyue Wang, Hao Yin

Institutions: Wuhan Ship Development & Design Institute, Beihang University, Civil Aviation University of China, China North Industries Group Corporation (China)

Language: English

Topic: Human-Automation Interaction and Safety

Subfield: Social Psychology

Field: Psychology

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $3,137

Funder: Civil Aviation University of China