Abstract:

With the arrival of the big data era, the application of big data technology in mineral exploration has become a trend for future development. This study systematically reviews the development of big data-based mineral exploration and integrated information prediction theories, explores the key technologies of big data in mineral prediction, and presents the following main conclusions based on practical case studies: First, big data mineral exploration can effectively address the challenges of increasing data volume and complexity, providing more accurate data interpretation and predictive support. Second, as a technological tool, big data mineral exploration must rely on solid mineral exploration theories, especially integrated information prediction theory. This theory not only provides theoretical support for big data methods but also improves the accuracy and efficiency of mineral resource predictions. Finally, based on integrated information prediction theory and using a convolutional neural network (CNN) model, mineral prediction for the Baiyinchagan Dongshan-Maodeng area in Inner Mongolia was conducted, demonstrating its application potential in mineral resource prediction. The research findings provide valuable references and practical experience for the application and theoretical development of big data in mineral exploration.

Key words: big data, mineral resource prediction, machine learning, integrated information mineral prediction, intelligent prediction