Hydrological Time Series Forecasting Model Based on Embedded Index

In this paper, we propose a hydrological time series forecasting model based onembedded index similarity search and LM algorithm improved BP neural network.The similarity search is used to mine the similar information from a large number of historical data, which can eliminate the redundancy and error information in the historical data, so as to reduce the number of training sets and improve the prediction accuracy.