Research on Motion Quality Evaluation and Simulation Modeling of Flexible Martial Arts Based on Fuzzy Bayesian Inference

While intelligently evaluating martial arts actions, we often face multiple uncertainties, such as video quality degradation, partial occlusion, and subjective evaluation fuzziness. Thus, the robustness and flexibility of the evaluation system are always restricted. To address these challenges, this study proposes a hybrid fuzzy Bayesian resilient simulation framework for dynamic complex systems. Through probabilistic modeling of the system state space, the framework transforms the action quality evaluation into the recursive estimation of the posterior confidence of the state, that is, the online inference of a dynamic Bayesian network is adopted to simulate the behavior trajectory of the system driven by uncertainty. Firstly, an improved double convolutional neural network is used to extract spatio-temporal features from video sequences accurately. Then, a fuzzy semantic quantification module is designed to map the quantitative features into qualitative evaluation grades to deal with the semantic fuzziness in the evaluation process. Finally, by using the previous state prior and the current fuzzy evidence, a dynamic Bayesian network is constructed to recursively infer the posterior state confidence with time continuity, which intends to maintain the stability of system inference when information is missing or contaminated. To further verify the flexibility of the framework, this study not only evaluates its basic recognition accuracy on the ActivityNet and THU-MOS14 datasets, but also designs the interference scenarios, including simulated physical occlusion and semantic boundary tampering. Besides, it also systematically tests the uncertainty tolerance and resilience of the model. The experimental findings show that the hybrid framework can not only maintain the recognition accuracy comparable to the advanced CNN baseline model, but also reduce the maximum attenuation of confidence by about 41.6% under simulated occlusion interference, and shorten the elastic recovery time by more than 50%. Thus, this study provides a theoretical basis and practical framework for the construction of a highly robust cyber physical simulation system for intangible cultural heritage protection and intelligent physical education teaching.