摘要
一位新闻记者-机器人与机器学习每日新闻的工作人员新闻编辑-调查人员发布了关于机器学习的新报告。根据《太原消息》，NewsRx记者的研究表明：“盆地磁性基底界面的反演对于解释势场资料和研究地热资源分布至关重要。”本文介绍了一种结合势场处理和机器学习技术的随机森林回归(RFR)算法反演磁性基底界面的新方法。本研究经费来自山西地质调查研究所有限公司。本报记者引用了太原理工大学的一篇研究文章：“该方法建立磁基界面模型，通过随机中点位移法和三维磁界面有限元正演模拟，对磁异常数据进行处理，然后利用方向变换、解析关联、空间导数和分数变换等技术，提取特征属性。”通过对理想化模型和噪声模型的分析,验证了该方法的有效性和实用性,该方法具有更高的智能性、高效性和更准确地反映磁基界面起伏的特点,并应用于大同盆地的磁测数据,验证了该方法的有效性和实用性.建立了与已知构造信息一致的可靠盆地基底模型，为进一步研究磁界面反演奠定了基础。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Investigators publish new report on Machine Learn ing. According to news originating from Taiyuan, People's Republic of China, by NewsRx correspondents, research stated, "Inversion of magnetic basement interfac es in basins is essential for interpreting potential field data and studying geo thermal resource distribution, as well as basin formation and evolution. This pa per introduces a novel method for inverting magnetic basement interfaces using a random forest regression (RFR) algorithm that combines potential field processi ng and machine learning techniques." Financial support for this research came from Shanxi Institute of Geological Sur vey CO., LTD.. Our news journalists obtained a quote from the research from the Taiyuan Univers ity of Technology, "The method creates magnetic base interface models and corres ponding magnetic anomaly data through the random midpoint displacement method an d magnetic interface finite element forward simulation. These anomalies are then processed using techniques such as directional transformations, analytical cont inuation, spatial derivatives, and fractional transformations. Feature attribute s are extracted, and Gini importance is utilized to measure the contributions of feature factors, identify effective features, and enhance algorithm efficiency. The validity and practicality of the method are demonstrated through the analys is of both idealized and noisy models. The proposed machine learning-based appro ach is more intelligent, efficient, and accurately represents the relief of magn etic base interfaces. When applied to magnetic survey data in the Datong Basin, it produced a reliable basin base model that aligns with known structural inform ation, paving the way for further research in magnetic interface inversion."
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