TY - DATA T1 - ARTIFICIAL NEURAL NETWORK MODELING OF PM10 AND PM2.5 IN A TROPICAL CLIMATE REGION: SAN FRANCISCO DE CAMPECHE, MEXICO PY - 2017/11/29 AU - Alberto Antonio Espinosa Guzmán AU - Oscar May Tzuc AU - Isaías Balam Pantí AU - Javier Reyes Trujeque AU - Ignacio Vicente Pérez Quintana AU - Ali Bassam UR - https://scielo.figshare.com/articles/dataset/ARTIFICIAL_NEURAL_NETWORK_MODELING_OF_PM10_AND_PM2_5_IN_A_TROPICAL_CLIMATE_REGION_SAN_FRANCISCO_DE_CAMPECHE_MEXICO/5634553 DO - 10.6084/m9.figshare.5634553 L4 - https://ndownloader.figshare.com/files/9813358 L4 - https://ndownloader.figshare.com/files/9813361 L4 - https://ndownloader.figshare.com/files/9813364 L4 - https://ndownloader.figshare.com/files/9813367 L4 - https://ndownloader.figshare.com/files/9813370 L4 - https://ndownloader.figshare.com/files/9813373 L4 - https://ndownloader.figshare.com/files/9813376 L4 - https://ndownloader.figshare.com/files/9813379 L4 - https://ndownloader.figshare.com/files/9813385 L4 - https://ndownloader.figshare.com/files/9813394 L4 - https://ndownloader.figshare.com/files/9813397 KW - atmospheric aerosols KW - air quality KW - mathematical modelling KW - artificial intelligence N2 - In this paper, a computational methodology based on Artificial Neural Networks (ANN) was developed to estimate the index of PM10 and PM2.5 concentration in air of San Francisco de Campeche city. A three layer ANN architecture was trained using an experimental database composed by days of the week, time of day, ambient temperature, atmospheric pressure, wind speed, wind direction, relative humidity, and solar radiation. The best ANN architecture, composed by 30 neurons in hidden layer, was obtained using the Levenberg-Marquardt (LM) optimization algorithm, logarithmic sigmoid and linear transfer functions. Model results generate predictions with a determination coefficient of 93.01% and 90.10% for PM2.5 and PM10, respectively. The proposed methodology can be implemented in several studies as public health, environmental studies, urban development, and degradation of historical monuments. ER -