Abstract:As a national major scientific engineering project, LAMOST currently has the highest observation and acquisition rate of the spectrum in the world, and provides a large amount of data and information resources for the research and development of astronomy. According to the stellar spectral data file released by LAMOST, the data about the wavelength of the stellar spectrum is extracted, and the data is subjected to noise culling, data dimensionality reduction, data normalization, and data dimensionality reduction processing. The BP neural network algorithm is used to classify the data, and the pros and cons of the BP neural network model are judged according to the correct rate of the classification results. However, the BP neural network test results of the test set data do not mean that it has the same test effect on other data and is easy to produce over-fitting, so the method of cross-validation combined with BP neural network is adopted. The BP neural network algorithm can test multiple sets of different data, obtain multiple sets of test results and obtain the average value, and obtain the relatively stable test results of the BP neural network model and reduce the randomness of the results.