AIMC Topic: Extreme Heat

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Comparative analysis of machine learning approaches for heatwave event prediction in India.

Scientific reports
Heatwaves, are identified as prolonged durations of unusually high temperatures, which pose significant threats to human health, animal health and agriculture. With the increasing frequency and intensity of heatwaves driven by climate change, accurat...

Extreme heat prediction through deep learning and explainable AI.

PloS one
Extreme heat waves are causing widespread concern for comprehensive studies on their ecological and societal implications. With the ongoing rise in global temperatures, precise forecasting of heatwaves becomes increasingly crucial for proactive plann...

Developing a seasonal-adjusted machine-learning-based hybrid time‑series model to forecast heatwave warning.

Scientific reports
Heatwaves pose a significant threat to environmental sustainability and public health, particularly in vulnerable regions and rapidly growing cities. They cause water shortages, stress on plants, and an overall drying out of landscapes, reducing plan...

Defining heatwave thresholds using an inductive machine learning approach.

PloS one
Establishing appropriate heatwave thresholds is important in reducing adverse human health consequences as it enables a more effective heatwave warning system and response plan. This paper defined such thresholds by focusing on the non-linear relatio...

A random forest model to predict heatstroke occurrence for heatwave in China.

The Science of the total environment
Extreme heat events have recently become more frequent and represent an increasing risk of damage to public health. However, the existing prediction of heatwave related health effects has limited representativeness and verification. Our study address...

Deep Learning Models for Health-Driven Forecasting of Indoor Temperatures in Heat Waves in Canada: An Exploratory Study Using Smart Thermostats.

Studies in health technology and informatics
In Canada, extreme heat occurrences present significant risks to public health, particularly for vulnerable groups like older individuals and those with pre-existing health conditions. Accurately predicting indoor temperatures during these events is ...