Machine Learning Modeling for Spatial-Temporal Prediction of Geohazard

Language: English

Published by MDPI AG, 2023

3036597867 / 9783036597867

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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nach der Bestellung gedruckt Neuware - Printed after ordering - Geohazards, such as landslides, rock avalanches, debris flow, ground fissures, and ground subsidence, pose a significant threat to people's lives and property. Recently, machine learning (ML) has become the predominant approach in geohazard modeling, offering advantages such as an excellent generalization ability and accurately describing complex and nonlinear behaviors. However, the utilization of advanced algorithms in deep learning remains poorly understood in this field. Additionally, there are fundamental challenges associated with ML modeling, including input variable selection, uncertainty quantification, and hyperparameter tuning. This reprint presents original research exploring new advances and challenges in the application of ML in the spatial-temporal modeling of geohazards. The contributions cover the susceptibility analysis of glacier debris flow and landslides, the displacement prediction of reservoir landslides, slope stability prediction and classification, building resilience evaluation, and the prediction of rainfall-induced landslide warning signals.

Seller Inventory # 9783036597867

Title
Machine Learning Modeling for Spatial-Temporal Prediction of Geohazard
Publisher
MDPI AG
Publication year
2023
Condition
Neu
Binding
Buch
Language
English
ISBN 10
3036597867
ISBN 13
9783036597867
Item weight
885 grams
Dimensions
250x175x22 mm

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

Shipping rates from Germany to U.S.A.

Item5 to 7 business days7 to 10 business days
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