Titlebook: Engineering Geology for a Habitable Earth: IAEG XIV Congress 2023 Proceedings, Chengdu, China; Volume 4: Technologi Sijing Wang,Runqiu Huan

Lasting

Application of Airborne Multispectral Remote Sensing Technology to Engineering Geological Mapping, in the accurate geological mapping of a large range and large scale. This technology not only provides a new idea for geological mapping of complex terrain areas, but also makes a contribution to promote the popularization and application of remote sensing technology.

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发芽

On Stability of a Slope with Bedrock Using the Upper Bound Limit Analysis,r. The effect of interface between bedrock and soil on the slope stability was discussed in detail. The equations for calculating safety factors for three possible failure modes of the slope with bedrock due to gravity were derived. The most dangerous failure mode of the slope was determined using a

HEAVY

Slope Displacement Prediction Based on Cross Distillation for Small Samples,s and the slope deformation time is long, there is few effective data that can be used for slope warning. For few effective samples, a lightweight prediction model based on knowledge distillation is established by introducing model compression to predict the slope displacement while improving the ti

CLAMP

A Novel Remote Sensing Landslide Semantic Segmentation Method: Using CycleGAN-Based Change DetectioDeep learning-based semantic segmentation algorithms often require a considerable amount of pixel-level labeled training data. In the study of landslide segmentation research, too high cost of labeling is a barrier to develop deep learning methods. Although the change detection method does not requi

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磨碎

阴谋

分解

Design of Landslide Monitoring System Based on Wireless Sensor Network, reliability, etc., this paper designs a landslide monitoring system based on wireless sensor network technology. The system takes micro-electromechanical system -based micro sensor technology, wireless communication technology and Zigbee wireless sensor network as the core, and collects data throug

Catheter

Prediction of Maximum Reinforcement Load of Reinforced Soil Retaining Walls Based on Machine Learnietaining walls. However, most of current theoretical methods can only consider limited factors due to no proper approach for considering more complex condition. In this study, by means of machine learning, 12 related factors affecting the reinforcement loads were chosen, and these factors are closel