[HTML][HTML] Using artificial intelligence to improve real-time decision-making for high-impact weather
Using Artificial Intelligence to Improve Real-Time Decision-Making for High-Impact Weather
in: Bulletin of the American Meteorological Society Volume 98 Issue 10 (2017) Jump to …
in: Bulletin of the American Meteorological Society Volume 98 Issue 10 (2017) Jump to …
A review of machine learning for convective weather
We present an overview of recent work on using artificial intelligence (AI)/machine learning
(ML) techniques for forecasting convective weather and its associated hazards, including …
(ML) techniques for forecasting convective weather and its associated hazards, including …
GIS-based rare events logistic regression for mineral prospectivity mapping
Mineralization is a special type of singularity event, and can be considered as a rare event,
because within a specific study area the number of prospective locations (1s) are …
because within a specific study area the number of prospective locations (1s) are …
Rare events and imbalanced datasets: an overview
M Maalouf, TB Trafalis - International Journal of Data Mining …, 2011 - inderscienceonline.com
Accurate prediction is important in data mining and data classification. Rare events data,
imbalanced or skewed datasets are very important in data mining and classification …
imbalanced or skewed datasets are very important in data mining and classification …
Robust weighted kernel logistic regression in imbalanced and rare events data
M Maalouf, TB Trafalis - Computational Statistics & Data Analysis, 2011 - Elsevier
Recent developments in computing and technology, along with the availability of large
amounts of raw data, have contributed to the creation of many effective techniques and …
amounts of raw data, have contributed to the creation of many effective techniques and …
[HTML][HTML] Classifying convective storms using machine learning
GE Jergensen, A McGovern… - Weather and …, 2020 - journals.ametsoc.org
Aggarwal, SK, and LM Saini, 2014: Solar energy prediction using linear and non-linear
regularization models: A study on AMS (American Meteorological Society) 2013–14 solar …
regularization models: A study on AMS (American Meteorological Society) 2013–14 solar …
Weighted logistic regression for large-scale imbalanced and rare events data
M Maalouf, M Siddiqi - Knowledge-Based Systems, 2014 - Elsevier
Latest developments in computing and technology, along with the availability of large
amounts of raw data, have led to the development of many computational techniques and …
amounts of raw data, have led to the development of many computational techniques and …
[HTML][HTML] Cry wolf effect? Evaluating the impact of false alarms on public responses to tornado alerts in the southeastern United States
On average, 75% of tornado warnings in the United States are false alarms. Although
forecasters have been concerned that false alarms may generate a complacent public, only …
forecasters have been concerned that false alarms may generate a complacent public, only …
Seismic liquefaction potential assessed by support vector machines approaches
X Xue, X Yang - Bulletin of Engineering Geology and the Environment, 2016 - Springer
Liquefaction of loose, saturated granular soils during earthquakes poses a major hazard in
many regions of the world. Determining the liquefaction potential of soils induced by …
many regions of the world. Determining the liquefaction potential of soils induced by …
Deep learning surrogate models of JULES-INFERNO for wildfire prediction on a global scale
S Cheng, H Chassagnon, M Kasoar… - … on Emerging Topics …, 2024 - ieeexplore.ieee.org
Global wildfire models play a crucial role in anticipating and responding to changing wildfire
regimes. JULES-INFERNO is a global vegetation and fire model simulating wildfire …
regimes. JULES-INFERNO is a global vegetation and fire model simulating wildfire …