D. Mendeleev University of Chemical Technology of Russia, Moscow, Russia:

A. F. Egorov, Head of a Chair of Computer-Integrated Systems in Chemical Technology
T. V. Savitskaya, Professor
V. A. Kolesnikov, Rector
Yu. A. Kuzmina, Post-Graduate Student, e-mail: julia.karibova@gmail.com

This article shows the functional structure of intelligent system for chemical products and technogenic waste hazard prediction and classification. The described intelligent system is a part of information-modeling system for monitoring and predicting of environmental state, and is designed to automate the collection of information, hazard classification of chemicals and technogenic waste, and labeling, based on classification results. There are described the methods of chemical hazard classification in deterministic manner (such as usage of fundamental physical laws and models), and in conditions of uncertainty, including prediction of unknown quantities, using neural networks, QSAR methodology and fuzzy logic, included in modeling subsystem. Neural network classification models and results are described together with possible uses of implemented approach. It is proposed to use the QSAR methodology to predict unknown data for investigated substance on available information about the properties of analogue substances. Use of fuzzy logic for hazard classification in conditions of uncertainty is substantiated. The generalized algorithm of hazard classification of chemicals (mixture substance) is shown in uncertainty conditions. The developed software module for waste classification is described, module interfaces are presented and example of its work is shown. Recommendations of intelligent system usage are proposed.

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