### Article

## Методы интеллектуального анализа в задачах оценки устойчивости ИКС к деструктивному воздействию ЭМИ

Analysis of existing approaches to the use of intelligent methods for solving the problem of destructive electromagnetic effects’ detection is performed. It is proposed to use an intelligent systems based on neural networks integrated with the means of fuzzy logic to detect the destructive electromagnetic effects on infocommunication system. Such approach will take into account a priori knowledge of subject area experts, and data of experimental studies.

The article discusses development of the segmented characters classifier of the Russian alphabet and of the Arabic numerals on the basis of block neural network structures including the plurality of blocks for each individual character recognition and for the synthesis block decision.

Soft Computing (SC) is a consortium of fuzzy logic (FL), neurocomputing (NC), evolutionary computing (EC), probabilistic computing (PC), chaotic computing (CC) and parts of machine learning theory (ML). SC is the foundation for computational intelligence and is leading to the development of numerous hybrid intelligent information, control and decision-making systems. The methodology of computing with words (CW) is an important event in the evolution of cognitive science, natural language processing, artificial intelligence, and different existing scientific theories. This is because CW can enrich the existing scientific theories and the above-mentioned science fields giving them the capability of using natural languages to operate on perception-based information, not only measurement-based information. Indeed in many real-world problems in natural sciences as well as in industrial engineering, economics, and business, often there is a need to deal with both perception and measurement based information. In the case of perception based information, the available information is not precise enough to justify the use of numbers. Such information is usually described in natural languages rather than in strict (idealized) mathematical expressions. So a strong need has appeared for a new approach, theory and technology for the development of knowledge representation, computing, and reasoning tools that allow creation of systems with high MIQ. The sessions of the ICSCCW-2011 will focus on the development and application of Soft Computing technology and computing with words paradigm in system analysis, decision and control.

We examine the questions of applying large pyramidal neural (intellectual neuron) networks to solve equipment object control problems. We consider the description of a system for dynamic planning of mobile robot behavior, constructed based on a network of similar elements.

The 8th conference of the European Society for Fuzzy Logic and Technology, EUSFLAT-2013, took place in Milan, the industrial and business capital of Italy. The EUSFLAT 2013 Conference was hold at the premises of the University of Milano-Bicocca, Milan, Italy from September 11th to September 13th, 2013. The aim of the conference is to bring together theoreticians and practitioners working on fuzzy logic, fuzzy systems, soft computing and related areas. It provide a platform for the exchange of ideas among scientists, engineers and students.

The way of the automated knowledge control system realization is offered on the basis of such intellectual means as the ontologic approach, fuzzy logic and data mining.

The Seventh International Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control aims at the development of Soft Computing and its Application is the Seventh of its kind. These fields have built upon mainly Fuzzy Logic originally introduced by L. Zadeh. Soft Computing (SC) is a consortium of fuzzy logic (FL), neurocomputing (NC), evolutionary computing (EC), probabilistic computing (PC), chaotic computing (CC) and parts of machine learning theory (ML). SC is the foundation for computational intelligence and is leading to the development of numerous hybrid intelligent information, control and decision making systems. The methodology of computing with words (CW) is an important event in the evolution of cognitive science, natural language processing, artificial intelligence, and different existing scientific theories. This is because CW can enrich the existing scientific theories and the above-mentioned science fields giving them the capability of using natural languages to operate on perception-based information, not only measurement-based information. Indeed, in many real-world problems in natural sciences as well as in industrial engineering, economics, and business, often there is a need to deal with both perception and measurement based information. In the case of perception based information, the available information is not precise enough to justify the use of numbers. Such information is usually described in natural languages or by means of visual images rather than in strict (idealized) mathematical expressions.So a strong need has appeared for a new approach, theory and technology for the development of knowledge representation, computing, and reasoning tools that allow creation of systems with high MIQ. The sessions of the ICSCCW-2013 will focus on the development and application of Soft Computing technology and computing with words paradigm in system analysis, decision and control.

A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.

Generalized error-locating codes are discussed. An algorithm for calculation of the upper bound of the probability of erroneous decoding for known code parameters and the input error probability is given. Based on this algorithm, an algorithm for selection of the code parameters for a specified design and input and output error probabilities is constructed. The lower bound of the probability of erroneous decoding is given. Examples of the dependence of the probability of erroneous decoding on the input error probability are given and the behavior of the obtained curves is explained.

Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability