Forecasting of Extreme Storm Tide Events Using NARX Neural Network-Based Models
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Forecasting of Extreme Storm Tide Events Using NARX Neural Network-Based Models
Authors
Keywords
-
Journal
Atmosphere
Volume 12, Issue 4, Pages 512
Publisher
MDPI AG
Online
2021-04-19
DOI
10.3390/atmos12040512
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Artificial Intelligence models for prediction of the tide level in Venice
- (2021) Francesco Granata et al. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
- Tide Prediction in the Venice Lagoon Using Nonlinear Autoregressive Exogenous (NARX) Neural Network
- (2021) Fabio Di Nunno et al. Water
- Accurate tide level estimation: A deep learning approach
- (2020) Amin Riazi OCEAN ENGINEERING
- Evapotranspiration evaluation models based on machine learning algorithms—A comparative study
- (2019) Francesco Granata AGRICULTURAL WATER MANAGEMENT
- Artificial intelligence based approaches to evaluate actual evapotranspiration in wetlands
- (2019) Francesco Granata et al. SCIENCE OF THE TOTAL ENVIRONMENT
- Real-time reservoir operation using recurrent neural networks and inflow forecast from a distributed hydrological model
- (2019) Shuyu Yang et al. JOURNAL OF HYDROLOGY
- The impact of operating the mobile barriers in Venice (MOSE) under climate change
- (2019) Georg Umgiesser JOURNAL FOR NATURE CONSERVATION
- Input selection and data-driven model performance optimization to predict the Standardized Precipitation and Evaporation Index in a drought-prone region
- (2018) Soukayna Mouatadid et al. ATMOSPHERIC RESEARCH
- Daily sea level prediction at Chiayi coast, Taiwan using extreme learning machine and relevance vector machine
- (2018) Moslem Imani et al. GLOBAL AND PLANETARY CHANGE
- Wave prediction using wave rider position measurements and NARX network in wave energy conversion
- (2018) Mohammed A.A. Desouky et al. APPLIED OCEAN RESEARCH
- Machine Learning Models for Spring Discharge Forecasting
- (2018) Francesco Granata et al. GEOFLUIDS
- The Use of NARX Neural Networks to Forecast Daily Groundwater Levels
- (2017) Sandra M. Guzman et al. WATER RESOURCES MANAGEMENT
- Flood forecasting within urban drainage systems using NARX neural network
- (2017) Yves Abou Rjeily et al. WATER SCIENCE AND TECHNOLOGY
- Simultaneous hydrological prediction at multiple gauging stations using the NARX network for Kemaman catchment, Terengganu, Malaysia
- (2016) Wei-Koon Lee et al. HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES
- Stream-flow forecasting using extreme learning machines: A case study in a semi-arid region in Iraq
- (2016) Zaher Mundher Yaseen et al. JOURNAL OF HYDROLOGY
- Support Vector Regression for Rainfall-Runoff Modeling in Urban Drainage: A Comparison with the EPA’s Storm Water Management Model
- (2016) Francesco Granata et al. Water
- Neuro-fuzzy and neural network techniques for forecasting sea level in Darwin Harbor, Australia
- (2012) Sepideh Karimi et al. COMPUTERS & GEOSCIENCES
- A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series
- (2009) Wen-Chuan Wang et al. JOURNAL OF HYDROLOGY
Create your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create NowAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started