Related references
Note: Only part of the references are listed.A General Framework for Uncertainty Estimation in Deep Learning
Antonio Loquercio et al.
IEEE ROBOTICS AND AUTOMATION LETTERS (2020)
Deep learning for time series classification: a review
Hassan Ismail Fawaz et al.
DATA MINING AND KNOWLEDGE DISCOVERY (2019)
A Meteorological Supersite for Aviation and Cold Weather Applications
Ismail Gultepe et al.
PURE AND APPLIED GEOPHYSICS (2019)
Statistical and Machine Learning forecasting methods: Concerns and ways forward
Spyros Makridakis et al.
PLOS ONE (2018)
Estimating meteorological visibility range under foggy weather conditions: A deep learning approach
Hazar Chaabani et al.
9TH INTERNATIONAL CONFERENCE ON EMERGING UBIQUITOUS SYSTEMS AND PERVASIVE NETWORKS (EUSPN-2018) / 8TH INTERNATIONAL CONFERENCE ON CURRENT AND FUTURE TRENDS OF INFORMATION AND COMMUNICATION TECHNOLOGIES IN HEALTHCARE (ICTH-2018) (2018)
A Neural network approach to visibility range estimation under foggy weather conditions
Hazar Chaabani et al.
8TH INTERNATIONAL CONFERENCE ON EMERGING UBIQUITOUS SYSTEMS AND PERVASIVE NETWORKS (EUSPN 2017) / 7TH INTERNATIONAL CONFERENCE ON CURRENT AND FUTURE TRENDS OF INFORMATION AND COMMUNICATION TECHNOLOGIES IN HEALTHCARE (ICTH-2017) / AFFILIATED WORKSHOPS (2017)
Using Reforecasts to Improve Forecasting of Fog and Visibility for Aviation
Gregory R. Herman et al.
WEATHER AND FORECASTING (2016)
Nowcasting visibility during wintertime fog over the airport of a metropolis of India: decision tree algorithm and artificial neural network approach
Debashree Dutta et al.
NATURAL HAZARDS (2015)
Prioritisation of software requirements using grey relational analysis
Abdel Ejnioui et al.
INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY (2013)
Fog Simulations Based on Multi-Model System: A Feasibility Study
Chune Shi et al.
PURE AND APPLIED GEOPHYSICS (2012)
Probabilistic Visibility Forecasting Using Bayesian Model Averaging
Richard M. Chmielecki et al.
MONTHLY WEATHER REVIEW (2011)
An Empirical Comparison of Machine Learning Models for Time Series Forecasting
Nesreen K. Ahmed et al.
ECONOMETRIC REVIEWS (2010)
An artificial neural network (p, d, q) model for timeseries forecasting
Mehdi Khashei et al.
EXPERT SYSTEMS WITH APPLICATIONS (2010)
Assessing the Impact of Weather on Traffic Intensity
Mario Cools et al.
WEATHER CLIMATE AND SOCIETY (2010)
Data-driven modelling: some past experiences and new approaches
Dimitri P. Solomatine et al.
JOURNAL OF HYDROINFORMATICS (2008)
A one-dimensional ensemble forecast and assimilation system for fog prediction
M. D. Mueller et al.
PURE AND APPLIED GEOPHYSICS (2007)
Ceiling and visibility forecasts via neural networks
Caren Marzban et al.
WEATHER AND FORECASTING (2007)
Fog research:: A review of past achievements and future perspectives
I. Gultepe et al.
PURE AND APPLIED GEOPHYSICS (2007)
Analysis of fog probability from a combination of satellite and ground observation data
Vincent Guidard et al.
PURE AND APPLIED GEOPHYSICS (2007)
Application of artificial neural network forecasts to predict fog at Canberra International Airport
Dustin Fabbian et al.
WEATHER AND FORECASTING (2007)
A new visibility parameterization for warm-fog applications in numerical weather prediction models
I. Gultepe et al.
JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY (2006)
The M3 competition: Statistical tests of the results
AJ Koning et al.
INTERNATIONAL JOURNAL OF FORECASTING (2005)
Fog prediction at Lisbon Airport using a one-dimensional boundary layer model
J Teixeira et al.
METEOROLOGICAL APPLICATIONS (2001)