Time Series Prediction Algorithm of Water and Sediment Flux Based on Spline Interpolation
The prediction of the variation trend of water and sediment flux is the basis of environmental governance along the Yellow River Basin.In view of the monitoring technology,the collected sediment flux data usually has a large number of missing values compared with the water flux data,which affects the accurate assessment of the variation of water and sediment flux.To solve this problem,the Nearest Neighbor,Linear,Quadratic Spline and Cubic Spline Interpolation methods are used to supplement the data,and the fitting error of the interpolation is compared.The experimental results show that the Cubic Spline Interpolation method is used to minimize the curve error,and the data after interpolation can better predict the future variation trend of water and sediment flux.
Big Data processingSpline Interpolationtime seriestrend prediction
万方数据
维普
