A Novel Model for Landslide Displacement Prediction Based on EDR Selection and Multi-Swarm Intelligence Optimization Algorithm

With the widespread application of machine learning methods, the continuous improvement of forecast accuracy has become an important task, which is especially crucial for landslide displacement predictions. This study aimed to propose a novel prediction model to improve accuracy in landslide predict...

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Veröffentlicht in:	Sensors (Basel, Switzerland) Jg. 21; H. 24; S. 8352
Hauptverfasser:	Zhang, Junrong, Tang, Huiming, Tannant, Dwayne D., Lin, Chengyuan, Xia, Ding, Wang, Yankun, Wang, Qianyun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 14.12.2021 MDPI
Schlagworte:	complete ensemble empirical mode decomposition (CEEMD) edit distance for real sequence (EDR) Genetic algorithms Geology landslide displacement prediction Landslides & mudslides multi-swarm intelligence (MSI) Noise Optimization algorithms Rain Signal processing Support vector machines support vector regression (SVR) Time series Wavelet transforms edit distance for real sequence (EDR) complete ensemble empirical mode decomposition (CEEMD) support vector regression (SVR) landslide displacement prediction multi-swarm intelligence (MSI)
ISSN:	1424-8220, 1424-8220
Online-Zugang:	Volltext
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