利用兰州地区环境空气质量监测点2015年的大气污染物和气象资料,对比分析了BP神经网络(BPNN)和支持向量机回归(SVR)模型对ρ(PM_(10))的预测效果,并选取典型重污染天气个例验证两种模型的适用性.结果表明, SVR全年和四季的逐2 h预测结果优于BPNN,两者在全年,春季和冬季2~24 h的平均绝对误差总体随着预测时段的增加...
Additionally, the generalization ability of the jacking force prediction models was examined using a new dataset, and the PSO-SVR model exhibited superior performance over the PSO-BPNN model. The study highlight...
利用K均值聚类及分段三次Hermite插值法,实现了样本数据的等距化;搭建LSTM-BPNN-SVR预测模型强化了对样本数据特征信息的提取,实现了对地铁车辆轴箱温度高精度预测的目的.通过与实测数据进行对比,该模型预测精度可达到99.15%,验证了该方法的有效性;通过与其他六种常规模型的预测结果对比,LSTM-BPNN-SVR预测模型具有更高的...
Hence, different algorithms (BPNN, SVR, RF, LSTM, LSTM-SVR) are utilized to perform multivariate non-Gaussian wind pressure conditional simulation and comparative analysis using prediction measures (MAPE, RMSE, R). In this paper, the non-Gaussian characteristics of the wind pressure data measured ...