Research on Data Mining Technology Based on Artificial Neural Networks
Xiaojiang Sun, Yiming Tang, Qingqing Luo, Yuzhi Chen, Moli Zhang · 2024
With the advancement of computer technology and communication technology, the level of informatization in various industries is increasing, and massive data is generated every moment. Conducting in-depth mining and analysis of this data can help promote the development of related industries. Data mining (DM) is a multidisciplinary field that utilizes knowledge from various disciplines such as statistics, machine learning, and database theory to extract and obtain data. As the most important time data, how to learn the historical patterns of time series and predict their future trends has always been a key research topic for scholars and has important application value. For the prediction of time series data, traditional methods mostly predict one or more specific values by analyzing historical data, but the accuracy of the predicted specific values is relatively low. Therefore, artificial neural network (ANN) models are used to address new issues that arise in time series prediction. This paper proposes an ANN based DM method to extract useful features and patterns from a large amount of temporal data through training and learning, in response to the characteristics of time series and nonlinearity in operational data. The experimental results show that the proposed method has high prediction accuracy and good application prospects.