基于卡口实时过车数据进行交通流量的实时预测分析，使用LSTM循环神经网络模型进行融合预测，准确率达到90%以上。
基于LSTM卡口实时过车数据进行交通流量的实时预测分析python源码(含数据和模型，准确率90%以上).zip
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2023-10-16
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基于LSTM卡口实时过车数据进行交通流量的实时预测分析python源码(含数据和模型，准确率90%以上).zip （62个子文件） 
TimeSeries_predict_rh.py 10KB main.py 592B tz.csv 1KB
dataset tcc_qb.csv 8.82MB tcc_qb_5.csv 19.03MB dataset_1.csv 105KB qb.csv 1.94MB tzz_10mint.csv 27.12MB qbb.csv 2.16MB tz_qb.csv 3.73MB real_error.py 12KB TimeSeries_predict_yc.py 5KB forecast_error.csv 146B model_15_0.0008 checkpoint 267B flow.model-2000.data-00000-of-00001 27KB flow.model-1500.meta 156KB flow.model-2000.meta 156KB flow.model-500.index 691B flow.model-1500.data-00000-of-00001 27KB flow.model-0.index 691B flow.model-0.meta 156KB flow.model-1000.meta 156KB flow.model-500.meta 156KB flow.model-1000.data-00000-of-00001 27KB flow.model-1500.index 691B flow.model-2000.index 691B flow.model-500.data-00000-of-00001 27KB flow.model-1000.index 691B flow.model-0.data-00000-of-00001 27KB tzz.csv 1KB result.csv 2KB model_30_0.0005 checkpoint 267B flow.model-2000.data-00000-of-00001 95KB flow.model-1500.meta 156KB flow.model-2000.meta 156KB flow.model-500.index 695B flow.model-1500.data-00000-of-00001 95KB flow.model-0.index 695B flow.model-0.meta 156KB flow.model-1000.meta 156KB flow.model-500.meta 156KB flow.model-1000.data-00000-of-00001 95KB flow.model-1500.index 695B flow.model-2000.index 695B flow.model-500.data-00000-of-00001 95KB flow.model-1000.index 695B flow.model-0.data-00000-of-00001 95KB model_10_0.0006 checkpoint 175B flow.model-500.index 690B flow.model-0.index 690B flow.model-0.meta 155KB flow.model-1000.meta 155KB flow.model-500.meta 155KB flow.model-1000.data-00000-of-00001 13KB flow.model-500.data-00000-of-00001 13KB flow.model-1000.index 690B flow.model-0.data-00000-of-00001 13KB data_processing.py 9KB __pycache__ TimeSeries_predict_rh.cpython-36.pyc 6KB data_processing.cpython-36.pyc 5KB t_predict.csv 2.32MB
项目介绍.txt 154B资源评论
