Using_Artificial_Intelligence_to_forecast_the_location_of_earthquake_and_post-earthquake-induced_landslides.pdf (5.01 MB)
Using Artificial Intelligence to forecast the location of earthquake and post-earthquake-induced landslides
presentation
posted on 2019-09-24, 02:57 authored by Rand HusoThis presentation will be on the progress we've made trying to forecast landslides caused by earthquakes and precipitation. Good quality input datasets are used to train a Tensorflow / Keras Sequential neural network whose parameters are determined by using Bayesian hyperparameter optimization (BayesianOptimization), and whose training details are established by using KFold (sklearn) iterations with the EarlyStopping monitor. The resulting trained neural network is then applied to all the available data, and some graphs are created to show the results.
Funding
History
Publisher
New Zealand eScience InfrastructureContact
nooriyah.lohani@nesi.org.nzSpatial coverage
New ZealandTemporal coverage: start
2019-09-05Temporal coverage: end
2019-09-06Usage metrics
Categories
No categories selectedLicence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC