The RNN technique used to calculate pollution load has a direct influence on quantifying pollution's impact on air quality and on the overall assessment results. As a result, the weight of each assessment criteria must be determined in a convoluted and thorough manner. This Fuzzy is engaged in...
environmental justice. As India grapples with the immediate consequences of air pollution, emerging challenges require attention. Also, climate change exacerbates existing issues, influencing weather patterns and contributing to the persistence of stagnant air masses that trap pollutants and their transportati...
Maps were created using Python 3 and geoplots. Full size image Instead of considering the full distribution of each site’s pollutants, in the following we will concentrate onto the tails. One reason for doing so is that we are particularly interested in the statistics of high pollution states...
Time Series Approach to Smart City Transformation: The Problem of Air Pollution in Brescia. AI 2024, 5, 17–37. [Google Scholar] [CrossRef] Dey, S. Urban Air Quality Index Forecasting Using Multivariate Convolutional Neural Network-Based Customized Stacked Long Short-Term Memory Model. Process ...
IQAir provides the world's largest free real-time air quality and pollution information platform from over 100.000 locations and cities. Query historical, current or even forecast data based on your subscription.This connector is available in the following products and regions:...
et al. Detection and attribution of wildfire pollution in the Arctic and northern midlatitudes using a network of Fourier-transform infrared spectrometers and GEOS-Chem. Atmos. Chem. Phys. 20, 12813–12851 (2020). Article CAS Google Scholar Zheng, B. et al. Increasing forest fire emissions ...
Detection and classification of trash using computer vision has been studied in a multitude of previous research applications. Thung and Yang presented a fine-tuned CNN for the classification of garbage with respect to their Trashnet dataset [12]. The classification accuracy of their prediction model...
Data were logged internally on the Q-Trak and downloaded after each run using the manufacturer's software (TrakPro, TSI, Inc.). The Q-Trak probe was 1.0 m from the ground. CO concentrations were generally below detection limit, and the few points when elevated concentrations were detected ...
As mentioned above, the ultimate goal of AQI prediction using the ADNNet is to minimize the prediction error by finding a nonlinear function F. We use the learning algorithm A to map a finite air pollution dataset DU into the function F and minimize the loss function L(DU;F;Θ). The le...
Weather recognition is crucial due to its significant impact on various aspects of daily life, such as weather prediction, environmental monitoring, tourism, and energy production. Several studies have already conducted research on image-based weather re