This article addresses the issue of having limited access to road traffic density and pollution concentration data by applying deep generative models, ...
May 17, 2021 · This article addresses the issue of having limited access to road traffic density and pollution concentration data by applying deep generative models.
This article addresses the issue of having limited access to road traffic density and pollution concentration data by applying deep generative models, ...
Urbanization trends worldwide show a clear preference for motorized road mobility, which has led to a degradation of air quality in recent years. Modelling ...
Resumen *. Urbanization trends worldwide show a clear preference for motorized road mobility, which has led to a degradation of air quality in recent years.
Generative adversarial networks to model air pollution under uncertainty. Toutouh, J., Nesmachnow, S., & Rossit, D. G. In Bychkov, I. V., Stojanov, Z.
Sep 7, 2024 · Modeling, predicting, and forecasting ambient air pollution is an important way to deal with this issue because it would be helpful for decision ...
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This work proposes to train models able to generate synthetic nitrogen dioxide daily time series according to a given classification that will allow an ...
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Dec 2, 2021 · In this paper, we develop a Generative Adversarial Network (GAN)-based method to model the complex and diverse residential load patterns and ...