Nowadays, artificial intelligence has entered into all spheres of our life. The system of analysis of the electronic environment is not an exception. However, there are a number of problems in the analysis of the electronic environment, namely the signals. They are analyzed in a complex electronic environment against the background of intentional and natural interference. Also, the input signals do not match the standards due to the influence of different types of interference. Interpretation of signals depends on the experience of the operator, the completeness of additional information on a specific condition of uncertainty. The best solution in this situation is to integrate with the data of the information system analysis of the electronic environment and artificial neural networks. Their advantage is also the ability to work in real time and quick adaptation to specific situations. These circumstances cause uncertainty in the conditions of the task of signal recognition and fuzzy statements in their interpretation, when the additional involved information may be incomplete and the operator makes decisions based on their experience. That is why, in this article, an improved method for finding solutions for neuro-fuzzy expert systems of analysis of the electronic environment is developed. Improving the efficiency of information processing (reducing the error) of evaluation is achieved through the use of neuro-fuzzy artificial neural networks that are evolving and learning not only the synaptic weights of the artificial neural network, but also the type and parameters of the membership function. High efficiency of information processing is also achieved through training in the architecture of artificial neural networks by taking into account the type of uncertainty of the information that has to be assessed and work with clear and fuzzy products. This reduces the computational complexity of decision-making and absence of accumulation of an error of training of artificial neural networks as a result of processing of the arriving information on an input of artificial neural networks. The use of the proposed method was tested on the example of assessing the state of the electronic environment. This example showed an increase in the efficiency of assessment at the level of 20–25 % on the efficiency of the processing information

The algorithm to train artificial neural networks for intelligent decision support systems has been constructed. A distinctive feature of the proposed algorithm is that it conducts training not only for synaptic weights of an artificial neural network, but also for the type and parameters of membership function. In case of inability to ensure the assigned quality of functioning of artificial neural networks due to training of parameters of artificial neural network, the architecture of artificial neural networks is trained. The choice of the architecture, type and parameters of membership function occurs taking into consideration the computation resources of the facility and taking into consideration the type and the amount of information entering the input of an artificial neural network. In addition, when using the proposed algorithm, there is no accumulation of an error of artificial neural networks training as a result of processing the information entering the input of artificial neural networks.Development of the proposed algorithm was predetermined by the need to train artificial neural networks for intelligent decision support systems in order to process more information given the unambiguity of decisions being made. The research results revealed that the specified training algorithm provides on average 16–23 % higher the efficiency of training artificial neural networks training that is on average by 16–23 % higher and does not accumulate errors in the course of training. The specified algorithm will make it possible to conduct training of artificial neural networks; to determine effective measures to enhance the efficiency of functioning of artificial neural networks. The developed algorithm will also enable the improvement of the efficiency of functioning of artificial neural networks due to training the parameters and the architecture of artificial neural networks. The proposed algorithm reduces the use of computational resources of decision support systems. The application of the developed algorithm makes it possible to work out the measures aimed at improving the effectiveness of training artificial neural networks and to increase the efficiency of information processing

The results of the development of a formalized mathematical model for describing the interaction of laser radiation with the plasma material intended to protect radio electronic means (REM) by reflecting this radiation are presented in this research. The basic structure of the physical model of solid-state radioisotope material is presented. It has been found out that the generation of the Langmuir noise in the protective layer of solid-state plasma of the screen of radio-electronic means provides shielding from laser radiation at a sufficiently small value of the field strength of the Langmuir wave. In this case, there is a re-emission of laser energy in the opposite direction.

The composition of airborne equipment is analyzed. It Indicates the need to solve the problem of protecting the board radio electronic means from the effects of powerful electromagnetic radiation.The article uses natural technologies to protect structural openings and board radio electronic means inputs from the effects of electromagnetic radiation. Board radio electronic means protection device was developed. Analytical conditions for board radio electronic means protection have been determined. Discharge criteria for guaranteeing board radio electronic means protection are proposed. It takes into account the powerful electromagnetic radiation parameters and the state of the ionized medium in the discharge point.

The article deals with the topicality of the question of development of fundamentally new means of protection of radio-electronic equipment based on the use of natural (plasma) technologies against the destructive effect of radio-frequency and optical (laser) radiation.The impact of the solid-state plasma media on the evolution of the impulse of radio-frequency and optical radiation has been studied and investigated.The impact of the solid-state plasma media on the passage of narrowband radio-frequency radiation and broadband impulse optical radiation has been estimated.