A multi-view ensemble machine learning approach for 3D modeling using geological and geophysical data

IF 4.3 1区地球科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

International Journal of Geographical Information Science Pub Date : 2024-08-22 DOI:10.1080/13658816.2024.2394228

Deping Chu, Jinming Fu, Bo Wan, Hong Li, Lulan Li, Fang Fang, Shengwen Li, Shengyong Pan, Shunping Zhou

引用次数: 0

Abstract

Geophysical data are often integrated into geological data for 3D modeling of underground spaces. However, the existing single-view approach means it is difficult to adequately fuse the valid infor...

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利用地质和地球物理数据进行三维建模的多视角集合机器学习方法

地球物理数据通常与地质数据相结合，用于地下空间的三维建模。然而，现有的单视角方法意味着很难充分融合有效信息。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Geographical Information Science 地学-计算机：信息系统

CiteScore

11.00

自引率

7.00%

发文量

审稿时长

9 months

期刊介绍： International Journal of Geographical Information Science provides a forum for the exchange of original ideas, approaches, methods and experiences in the rapidly growing field of geographical information science (GIScience). It is intended to interest those who research fundamental and computational issues of geographic information, as well as issues related to the design, implementation and use of geographical information for monitoring, prediction and decision making. Published research covers innovations in GIScience and novel applications of GIScience in natural resources, social systems and the built environment, as well as relevant developments in computer science, cartography, surveying, geography and engineering in both developed and developing countries.