Visual recognition and prediction analysis of China's real estate index and stock trend based on CNN-LSTM algorithm optimized by neural networks.

ABSTRACT: Today, with the rapid growth of Internet technology, the changing trend of real estate finance has brought great an impact on the progress of the social economy. In order to explore the visual identification (VI) effect of Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM) algorithm based on neural network optimization on China's real estate index and stock trend, in this study, artificial neural network (ANN) algorithm is introduced to predict its trend. Firstly, LSTM algorithm can effectively solve the problem of vanishing gradient, which is suitable for dealing with the problems related to time series. Secondly, CNN, with its unique fine-grained convolution operation, has significant advantages in classification problems. Finally, combining the LSTM algorithm with the CN

SUBMITTER: Chen N 

PROVIDER: S-EPMC9955670 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature