Intelligent Prediction and Optimization Algorithm of Informatization Project Progress Driven by Big Data

With the increasing scale and complexity of information-based projects, accurate progress prediction and an effective optimization algorithm are crucial to the success of the project. In this article, the authors focus on the schedule management of information projects driven by big data, build a schedule prediction model based on a long short-term memory network through in-depth study of relevant basic theories, and design an optimization algorithm based on the principle of heuristic algorithm. In the experimental verification stage, the data of 50 informatization projects in different industries were selected. After training and testing, the authors used the proposed model to predict that mean absolute error is 3.5, root mean square error is 4.8, and mean absolute percentage error is 5.2%. After optimization, the average duration of the project is shortened by 20%.