In recent years, digital visualization technology of intangible cultural heritage has attracted extensive attention. With efficient digital visualization methods, it can reflect the colorful living history and culture of human beings from multiple angles. It is an inevitable development trend to use digital technology to protect and promote intangible cultural heritage. This paper takes cultural space as the core element, based on conceptual abstraction, object type division and information characteristic analysis, and uses the related concepts and algorithms of long short-term memory model (LSTM) to digitally model the intangible cultural heritage information space. In this paper, the computer intelligence algorithm is used to train the LSTM data set, and the node parameters in the LSTM are mapped to the corresponding weight vector and bias vector, and then the solution space with the mean absolute error as the objective function is constructed, and the computer intelligence algorithm is used to optimize in the digital space. The experimental results show that the mean square error (MSE) results of training LSTM based on the computer intelligence algorithm show that the prediction accuracy of the training set, test set 1 and test set 2 of the gray wolf optimization algorithm (GWO) is 87.82%, 45.55%, 58.22%, the training set prediction accuracy of IGWO-GA algorithm is 98.85%. Moreover, the error between the prediction results and the actual value in the training set and test set is low, indicating that the improvement effect is good. It verifies the advantages and feasibility of LSTM digital model in organizing and expressing intangible cultural heritage digital information.

Huixia Yu, Zhenfu Mao and Faxian Jia. Digital Visualization of Intangible Cultural Heritage Based on Computer Intelligent Algorithm. International Journal of Art Innovation and Development (2024), Vol. 5, Issue 1: 15-31. https://doi.org/10.38007/IJAID.2024.050102.

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