Optimal selection method for spraying measures on concrete bin surface of dam in high-temperature season

The invention provides a high-temperature season dam concrete bin surface spraying measure optimization method, which comprises the following steps of S1, optimizing spraying influence factors, and constructing different spraying factor combination working conditions by adopting an orthogonal design principle according to the value range of the spraying influence factors; s2, carrying out a spraying test on each spraying factor combination working condition, monitoring to obtain a temperature space-time distribution rule in a spraying area, and forming a learning sample by the spraying factor combination working condition and the corresponding actually measured temperature space-time distribution; s3, the Attention-LSTM neural network model is trained and checked by using the learning sample, and the Attention-LSTM neural network model with the optimal nonlinear mapping relation is obtained; and S4, designing and determining a spray cooling effect evaluation index, establishing a multi-objective planning mode