Research on Multidimensional Data Prediction Method Based on Deep Neural Network

This topic is dedicated to studying the multidimensional data prediction technology based on deep neural networks, including data preprocessing, data standardization, dimensionality reduction processing, and the construction and training process of deep learning neural networks. In the specific implementation process, in the field of data processing, this study adopted convolutional neural network (CNN) and multilayer deep neural network (DNN) technology. This model significantly improved the training efficiency and prediction accuracy by implementing dimensionality reduction strategies such as standardization and principal component analysis. The research data revealed that the constructed model has a significant ability to interpret data variability when performing regression analysis tasks, and both the mean square error and the coefficient of determination show excellent performance; in the field of data classification, the accuracy and F1 value of the model have reached a high level. The model shows high-precision prediction ability when processing complex multidimensional data. The multidimensional data prediction model based on deep learning technology shows significant practical value and high efficiency.