摘要
气流走向和风速变化对危险化学气体泄漏的走势有重要影响。基于此,提出神经网络结合的环境敏感监测模型,采用PSO-BP神经网络、GA-BP神经网络、ABC-BP神经网络进行的预测值与实际数据数值进行对比,并模拟气体泄漏后的短期风速的趋势。研究发现,ABCBP神经网络算法可以在最短的时间内做出反馈,提高预测精度并将预测误差率控制到最低。
Changes in air direction and wind speed have important effects on the tendency of hazardous chemical gas leakage.Based on this,an environmental sensitivity monitoring model combined with the neural network was proposed.The predicted values of pso-bp neural network,ga-bp neural network and abc-bp neural network were compared with the actual data values,and the short-term wind speed trend after gas leakage was simulated.The study found that the ABC-BP neural network algorithm can make feedback in the shortest time,improve the prediction accuracy,and control the prediction error rate to the minimum.
作者
刘涛
LIU Tao(Fuyang College of Vocational Technology,Fuyang Anhui,236031,China)
出处
《佳木斯大学学报（自然科学版）》
CAS
2019年第1期54-56,共3页
Journal of Jiamusi University：Natural Science Edition
基金
安徽省高校自然科学重点研究项目(KJ2017A606)
