Approaches for Assessing the Polymetallic Impact on Humans in an Urbanized Area Using Neural Network Modeling Methods

Abstract

A methodology for assessing the response to the polymetallic effects of sensitive population groups has been developed using new information methods and data collection paths used for evaluation. The presented methodology takes into account the processes of polymeric intake, accumulation in the environment, and biosubstrates of the human body. The approach is presented for simultaneous accounting and analysis of dissimilar and heterogeneous data having different degrees of influence on the content of metals in human biosubstrates and the investigated components of the environment using neural self-organizing network Kohonen, implemented in the author’s model of neuronetwork filtration. A method of determining probability of exceeding the threshold values of metal concentrations in the objects under investigation using the risk theory is proposed. As the thresholds of these events, we have taken the median of continuous series of observations of metal concentrations. The facts of established exceeding the thresholds (events) were recorded in the whole set of observations, allocated in the form of clusters formed by the help of neural network classification. In this case, the spatial distribution of selected observations having specific address mappings forms the corresponding territorial zones, which can be used for operational and planned quality management of environmental components in an urbanized territory.