Algorithm optimization and application analysis in mineral resource exploration

Algorithm optimization plays a crucial role in improving the efficiency and accuracy of mineral resource exploration. Through the improvement of traditional exploration algorithms and the introduction of deep learning methods, a multi-source data fusion analysis model suitable for complex geological conditions has been established. Research shows that the optimized algorithm has achieved significant improvements in target recognition accuracy, computational efficiency, and resource consumption, with average recognition accuracy increasing by 15.3% and computation time reducing by 37.2%. By adopting adaptive parameter adjustment strategies for different geological structure characteristics, the algorithm's generalization ability and practical value have been further enhanced, providing new technical support for the modernization of mineral resource exploration.