Application of Artificial Intelligence Technology in Intelligent Building Decoration Management

Building decoration construction management is a more complex project, we must do a good job in the actual construction management, accumulate relevant construction experience, standardize construction procedures, and ensure the overall quality of project construction. In this paper, BPNN(Back Propagation neural network) method is used to predict the fatigue life of decoration materials, and GA (Genetic Algorithm) is introduced to optimize it and establish the prediction model; a numerical example is used to train and test the model. In this paper, by comparing the training effect of the network, selecting the appropriate network parameters, and comparing the predicted values with the calculated values obtained by the traditional method, the advantages of this model in predicting the fatigue life of materials are verified. The results show that the test set accuracy of GA-BP algorithm model is the highest, while the training set accuracy of BP algorithm is as high as $\mathbf{9 9 \%}$, and the test set accuracy is only $\mathbf{7 0 \%}$, which shows overfitting phenomenon.