基于特征参数的任务可用能力评估

Task Availability Capability Assessment Based on Characteristic Parameters

针对实时故障特征参数输入情况下评估系统任务能力的问题,文中提出了一种基于特征参数的任务可用能力评估方法。通过引入神经模糊系统(NFS)建立航保系统易损性模型,将模糊规则融入神经网络框架中,建立了系统任务可用能力评估模型。该方法结合了模糊逻辑的推理能力和神经网络的无限逼近函数能力,创建了真实系统的替代模型,具有更高的普适性。利用智能优化算法使替代模型尽可能接近真实模型,摆脱了系统中未知权重系数依赖于专家或经验的限制,为模糊神经网络(FNN)赋予了学习能力。实验结果和分析表明该评估模型全面而合理,该方法可以扩展应用于水下领域,评估航保系统和舰船系统的任务能力。

To evaluate system task availability under the condition of real-time fault feature parameter input,a method ofassessing task availability capability based on characteristic parameters was proposed.By introducing the neuro-fuzzysystem(NFS),a vulnerability model of the aviation insurance system was established,and fuzzy rules were integrated into theframework of neural networks to establish an assessment model for system task availability capability.This method combinedthe reasoning ability of fuzzy logic and the infinite approximation function ability of neural networks to create an alternativemodel of the real system,which was more universal.Moreover,an intelligent optimization algorithm was used to make thealternative model approach to the real model,getting rid of the influence of unknown weight coefficients in the system thatrelied on experts or experience and endowing the fuzzy neural network(FNN)with learning capabilities.The experimentalresults and analysis show that the assessment model is comprehensive and reasonable and can be extended to the underwaterfield to assess the mission capabilities of navigation support systems and naval ship systems.