Related papers: Predicting Long-term Urban Overheating and Their M…
In this research, we develop machine learning models to predict future sensor readings of a waste-to-fuel plant, which would enable proactive control of the plant's operations. We developed models that predict sensor readings for 30 and 60…
The increasing global demand for clean and environmentally friendly energy resources has caused increased interest in harnessing solar power through photovoltaic (PV) systems for smart grids and homes. However, the inherent unpredictability…
In building management, usually static thermal setpoints are used to maintain the inside temperature of a building at a comfortable level irrespective of its occupancy. This strategy can cause a massive amount of energy wastage and…
Urbanization has a strong impact on the health and wellbeing of populations across the world. Predictive spatial modeling of urbanization therefore can be a useful tool for effective public health planning. Many spatial urbanization models…
Efforts to green cities for cooling are succeeding unevenly because the same vegetation that cools surfaces can also intensify how hot the air feels. Previous studies have identified humid heat as a growing urban hazard, yet how…
Understanding extreme events and their probability is key for the study of climate change impacts, risk assessment, adaptation, and the protection of living beings. Forecasting the occurrence probability of extreme heatwaves is a primary…
In this paper, we estimate the effect of heat stress index (a measure which takes into account rising temperatures as well as humidity) on data center energy consumption. We use forecasting models to predict future energy use by data…
Heat, Ventilation and Air Conditioning (HVAC) systems play a critical role in maintaining a comfortable thermal environment and cost approximately 40% of primary energy usage in the building sector. For smart energy management in buildings,…
Thermal management in the hyper-scale cloud data centers is a critical problem. Increased host temperature creates hotspots which significantly increases cooling cost and affects reliability. Accurate prediction of host temperature is…
Urbanization has a large impact on human society. Besides, global warming has become an increasingly popular topic since global warming will not only play a significant role in human beings daily life but also have a huge impact on the…
A significant challenge in seasonal climate prediction is whether a prediction can beat climatology. We hereby present results from two data-driven models - a convolutional (CNN) and a recurrent (RNN) neural network - that predict 2 m…
Extreme weather events are increasing in frequency and intensity due to climate change. This, in turn, is exacting a significant toll in communities worldwide. While prediction skills are increasing with advances in numerical weather…
Heatwaves are intensifying as a major climate extreme and have emerged as a growing public health threat in rapidly urbanizing regions such as India. In this study, we integrate long-term heat-related mortality records (1970-2023) with…
Beyond the immediate biophysical benefits, urban trees play a foundational role in environmental sustainability and disaster mitigation. Precise mapping of urban trees is essential for environmental monitoring, post-disaster assessment, and…
Wildfire frequency is increasing as the climate changes, and the resulting air pollution poses health risks. Just as people routinely use hourly weather forecasts to plan their day's activities around precipitation, reliable hourly air…
Nowadays, environmental protection has become a global consensus. At the same time, with the rapid development of science and technology, urbanisation has become a phenomenon that has become the norm. Therefore, the urban greening…
Climate change is expected to aggravate wildfire activity through the exacerbation of fire weather. Improving our capabilities to anticipate wildfires on a global scale is of uttermost importance for mitigating their negative effects. In…
Climate change is accelerating the frequency and severity of unprecedented events, deviating from established patterns. Predicting these out-of-distribution (OOD) events is critical for assessing risks and guiding climate adaptation. While…
With the press of global climate change, extreme weather and sudden weather changes are becoming increasingly common. To maintain a comfortable indoor environment and minimize the contribution of the building to climate change as much as…
Weather forecasting centers currently rely on statistical postprocessing methods to minimize forecast error. This improves skill but can lead to predictions that violate physical principles or disregard dependencies between variables, which…