Landslide Displacement Prediction Method Based on GA-Elman Model
The deformation process of landslide displacement has complex nonlinear characteristics. In view of the problems of large error, slow convergence and poor stability of the traditional neural network prediction model, in order to better realize the accurate and effective prediction of landslide displ...
Enregistré dans:
Auteurs principaux: | Chenhui Wang, Yijiu Zhao, Libing Bai, Wei Guo, Qingjia Meng |
---|---|
Format: | article |
Langue: | EN |
Publié: |
MDPI AG
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/cc6ba143f4e74f70a903fb4e9b6ff4c3 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Enhancement of nitrogen prediction accuracy through a new hybrid model using ant colony optimization and an Elman neural network
par: Pavitra Kumar, et autres
Publié: (2021) -
Modified Elman Neural-PID Controller Design for DC-DC Buck Converter System Based on Dolphin Echolocation Optimization
par: Khulood E. Dagher
Publié: (2018) -
Apriori association rule and K-means clustering algorithms for interpretation of pre-event landslide areas and landslide inventory mapping
par: Kusak Lutfiye, et autres
Publié: (2021) -
Comparison of Tree-Structured Parzen Estimator Optimization in Three Typical Neural Network Models for Landslide Susceptibility Assessment
par: Guangzhi Rong, et autres
Publié: (2021) -
A Novel Parallel Processing Model for Noise Reduction and Temperature Compensation of MEMS Gyroscope
par: Qi Cai, et autres
Publié: (2021)