Forecasting is an international academic journal dedicated to the field of predictive science, covering research in multiple disciplines such as time series analysis, econometrics, statistics, and machine learning. This journal aims to publish cutting-edge research papers that explore the development, applications, and implementation effects of predictive models in different fields. Its content is not limited to theoretical research, but also includes empirical analysis and case studies, which help improve the accuracy and reliability of predictions and are of great significance for business decision-making, policy-making, and risk management.
The readership of the journal includes scholars, researchers, analysts, decision-makers, and students interested in predictive science. By publishing high-quality research results, the journal promotes communication and cooperation between academia and industry in the field of prediction. The journal adopts a peer review process to ensure that published articles meet international academic standards and make significant contributions to the development of predictive science. One of its characteristics is its focus on emerging technologies and methodologies, which enables the journal to reflect the latest developments in the field of predictive science. In addition, the journal encourages interdisciplinary research to solve complex prediction problems and promote innovation in the practical application of prediction models.