Aug 31, 2022 · This study compares two approaches and introduces a model suitable for the task of forecasting changes in hail frequency for ongoing decades.
Sep 30, 2023 · This study aims to develop a machine-learning model capable of working with various climatic models and climate change scenarios.
Sep 30, 2023 · This study compares the effectiveness of these two approaches and introduces a model suitable for forecasting changes in hail frequency.
Aug 31, 2022 · This study compares two approaches and introduces a model suitable for the task of forecasting changes in hail frequency for ongoing decades.
Hail risk assessment is crucial for businesses, particularly in the agricultural and insurance sectors, as it helps estimate and mitigate potential losses.
Long-term hail risk assessment with deep neural networks ... But there are no machine learning models for data-driven forecasting of changes in hail frequency for ...
Mar 11, 2024 · Hail losses are estimated by simulating 10 000 years of hail events with a Monte Carlo approach and us- ing three separate impact functions for ...
Our neural network exhibited strong discrimination between hail-days and non-hail days on a random validation set of 100,000 space-time grid points, with an ...
Radar and environment-based hail damage estimates using machine ...
www.researchgate.net › ... › Hail
Dec 9, 2024 · We use these datasets coupled with environmental information to calculate a hail damage estimate (HDE) using a deep neural network approach ...
Sep 27, 2023 · Research shows that small hailstone impacts can significantly reduce a roof's lifespan and make it more vulnerable to future hail events.