矿产资源勘查中成矿预测模型构建与精度提升研究

Research on the Construction and Accuracy Improvement of Mineralization Prediction Models in Mineral Resource Exploration

摘要

矿产资源勘查中的成矿预测是提高勘查效率和准确性的重要手段。随着矿产勘查需求的不断提升，传统的成矿预测方法面临着精度和效率的挑战。本文主要研究矿产资源勘查中成矿预测模型的构建与精度提升。通过对成矿预测的基本概念与发展历程进行分析，探讨了数据采集与处理、算法选择与优化等关键技术。重点分析了影响成矿预测精度的因素，如地质数据的质量与完整性、模型参数的选择与调整以及外部环境因素的影响。同时，本文还提出了多元化数据融合、机器学习与人工智能的应用以及交叉验证与精度评估方法作为提升预测精度的有效途径。

Abstract

Mineral resource exploration’s mineralization prediction is a crucial means to enhance exploration efficiency and accuracy.As the demand for mineral exploration continues to grow,traditional mineralization prediction methods face challenges in terms of precision and efficiency.This paper primarily investigates the construction of mineralization prediction models and their accuracy improvement in mineral resource exploration.By analyzing the basic concepts and development history of mineralization prediction,the paper explores key technologies such as data collection and processing,algorithm selection,and optimization.It focuses on factors affecting prediction accuracy,such as the quality and completeness of geological data,model parameter selection and adjustment,and the influence of external environmental factors.Additionally,this paper proposes the use of diversified data fusion,machine learning and artificial intelligence applications,as well as cross-validation and accuracy evaluation methods as effective ways to enhance prediction precision.

关键词

矿产资源勘查 / 成矿预测 / 数据处理 / 机器学习 / 精度提升

Key words

Mineral resource exploration / Mineralization prediction / Data processing / Machine learning / Accuracy improvement

参考文献

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