Strong-wind high-speed railway along-the-line wind speed space network structure prediction method

The invention discloses a strong-wind high-speed railway along-the-line wind speed space network structure prediction method. The wind speed is predicted by building an optimal weighted combined model based on three prediction models, wherein the first prediction model uses the short-term historical wind speed data of multiple anemometer stations, the second prediction model uses the short-term historical wind speed data of a single anemometer station, and the third prediction model uses the historical wind speed data of multiple anemometer stations and the corresponding historical meteorological data. The method integrates multiple elements including space, time and weather, makes use of a plurality of data including current data of an auxiliary anemometer station and a target anemometer station, historical meteorological data of the auxiliary anemometer station and the target anemometer station and wind speed data, and ensures the diversity of data. Temporal correlation and spatial correlation are combined organically, which improves the prediction reliability. As the data of the three basic models is interleaved, the amount of calculation is reduced. The prediction stability is high, multi-step advance prediction is realized, and the method has engineering application value.