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the article deals with information and technical support of the forest fire suppression process. The status update on the problem is considered. The necessity of using modern information decision-making systems in the process of forest fires suppression is substantiated. Improvement of the method of a decision support system constructing using MVC coding patterns is proposed.

In this paper, the hybrid multidimensional wavelet-neuro-system for pattern recognition tasks is proposed. Also learning algorithm for all its parameters (synaptic weights, the centers, and widths of wavelet activation functions) based on cross entropy cost function was proposed. The proposed system is characterized by high learning speed and high approximation properties in comparison with wellknown approaches. The efficiency of the proposed approach has been justified based on different benchmarks and real data sets.