基于CAPSO-BPNN的铁路信号运行状态预警方法研究

Study on the Precautionary Method for Railway Signal Running State Based on CAPSO-BPNN

为提高铁路信号运行状态预警的准确率,克服BPNN模型存在收敛速度慢和局部最优的缺点及其性能易受网络的初始权值、阈值等参数选择的影响,本文提出一种基于CAPSO-BPNN的铁路信号运行状态预警模型。结果表明,与PSO-BPNN和BPNN相比较,CAPSO-BPNN模型具有更高的预警准确率和更优的性能,为铁路信号运行状态预警提供了新的方法和途径。

In order to improve the precautionary accuracy for railway signal running state and overcome disadvantages of slow convergence speed and local optimization in BPNN model,and its performance was easily affected by the initial weight value and threshold value and so on,this paper proposed a precautionary model based on CAPSO-BPNN for railway signal running state.The results showed that the CAPSO-BPNN model had higher accuracy and better performance than PSO-BPNN and BPNN,which provided new method and approach for forewarning of the operating state of railway signals.