Data Mining of Fertility Intention based on LSTM Neural Network

In this paper, a method of data mining is proposed to predict fertility intention. The development of artificial intelligence has also further improved the security and efficiency of data processing. This paper introduces long short-term memory (LSTM) neural networks in deep learning. The advantage of LSTM neural networks is that they are suitable for studying time-dependent data. This paper uses data preprocessing, data completion, and prediction based on the LSTM neural network to improve and analyze fertility intention data. The overall process of this method can be divided into three steps: first, the original data set is collected and sorted out, and then the preprocessing is carried out. Common Method Bias and the Harman single factor test determined the preprocessed data. Finally, the LSTM neural network model is established to verify the data.