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Construction of PMx Concentration Surfaces Using Neural Evolutionary Fuzzy Models of Type Semi Physical Class

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Artificial Neural Network Modelling

Part of the book series: Studies in Computational Intelligence ((SCI,volume 628))

Abstract

Pollution by particulate matter (PMx) is the accumulation of tiny particles in the atmosphere due to natural or anthropogenic activities. Particulate matter becomes a pollutant that seriously affects the health of people. In order to reduce its concentration (PMx), understanding its behavior in space is necessary, overcoming both physical and mathematical limitations. Limitations here refer to little information that a set of monitoring stations provided with regard to air quality and with respect to the dynamics of a pollutant. Furthermore, to the effect that an emission source produces within a certain area (source apportionment). Therefore, this work proposes the development of a model for spatial analytical representation of PMx concentration over time as fuzzy information. The design of the model is inspired by the structure of a Self-Organizing Map (SOM). The model consists of an input layer (n_sources) and an output layer (m_stations) that were determined in shape and size for the study area. Connections between layers are defined by a Lagrangian backward Gaussian puff tracking model, which depend on the meteorological dynamics of the area. The model allows the estimation of emissions in n_sources, based on the measurement of (PMx) concentration in the m_stations that were considered. The connection weights are adjusted by using evolutionary algorithms. The model showed a series of analytical forecasting maps that describe the spatial temporal behavior of PMx concentration in terms of the puffs emitted by n_sources. The result is a spatial neural evolutionary fuzzy model of type semi-physical class. Its application can support the improvement of air quality in an study area.

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Authors and Affiliations

  1. Grupo de Investigación en Modelamiento Computacional y Simulación (GISMOC), Escuela de Ingeniería de Antioquia, Envigado Colombia, Km2 + 200 Mts. Variante al Aeropuerto José María Córdova, Envigado, Antioquia, Colombia

    Alejandro Peña

  2. Grupo de Investigación en Inteligencia Computacional (GIIC), Universidad Nacional de Colombia, Sede Medellín, Colombia

    Jesús Antonio Hernández

Authors
  1. Alejandro Peña
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  2. Jesús Antonio Hernández
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Correspondence to Alejandro Peña .

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Editors and Affiliations

  1. School of Computer and Mathematical, Auckland University of Technology (, Auckland, New Zealand

    Subana Shanmuganathan

  2. Dept of Informatics & Enabling Tech, Lincoln University, Lincoln, New Zealand

    Sandhya Samarasinghe

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Peña, A., Hernández, J.A. (2016). Construction of PMx Concentration Surfaces Using Neural Evolutionary Fuzzy Models of Type Semi Physical Class. In: Shanmuganathan, S., Samarasinghe, S. (eds) Artificial Neural Network Modelling. Studies in Computational Intelligence, vol 628. Springer, Cham. https://doi.org/10.1007/978-3-319-28495-8_15

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  • DOI: https://doi.org/10.1007/978-3-319-28495-8_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28493-4

  • Online ISBN: 978-3-319-28495-8

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