ComputingData ScienceForecastingMachine LearningTime Series AnalysisReal-time ForecastingTime Series ForecastingTime Series PredictionTraffic EngineeringTraffic Flow AnalysisTraffic Flow TheoryAccuracyReal-time RequirementsReal-time Traffic ForecastingShort-term Traffic PredictionTraffic Flow ForecastingTraffic Flow PredictionTraffic ForecastingTraffic Prediction
Although short term traffic flow forecasting algorithm is widely used today,some questions still exist. To address these issues, here an KNN NPR(K Nearest Neighbors Non Parametric Regression) based integrated algorithm which can make traffic flow forecasting and traffic event detection at the same time is proposed. Then in order to improve the accuracy and computing speed of the proposed algorithm, authors put forward two improvements which are improved in variable K search method based on “dense degree” and advanced data structures based on dynamic cluster method and hash function transformation.Field test fully proves two improvements, which the proposed algorithm can adequately meet real time system requirements and accuracy requirements.