Scientific Journal of KubSAU

At present, databases of 27-year observations of various adverse weather conditions and dangerous hydrometeorological phenomena leading to social and economic losses on the territory of Russia are in full open free access. Some of these natural hazards also cause significant damage to agriculture, especially crop production, horticulture and viticulture. Therefore, a great scientific and practical interest is the intellectual analysis of these data, which will create more favorable conditions for the prediction of such adverse events and decision-making, taking into account their possible negative impact on human activity. To achieve this goal, it is necessary to solve the following tasks, which are obtained by decomposition of the goal and are the stages of its achievement: Task 1: cognitive structuring of the subject area. Task 2: preparation of initial data and formalization of the subject area. Task 3: synthesis and verification of statistical and system-cognitive models and selection of the most reliable model. Task 4: solving problems in the most reliable model: - subtask 4.1. Forecasting (diagnostics, classification, recognition, identification); - subtask 4.2. Support decision-making; - sub-task 4.3. Study of the simulated subject area by studying its model (cognitive diagrams of classes and values of factors, agglomerative cognitive clustering of classes and values of factors, nonlocal neurons and neural networks, 3d-integral cognitive maps, cognitive functions). It is proposed to use automated system-cognitive analysis (ASC-analysis) to solve the tasks. The article provides a detailed numerical example illustrating the solution of all these problems

The Euler function is very important in number theory and in Mathematics, however, the range of its values in the natural numbers has not been written off. The greatest value of the Euler function reaches on Prime numbers, furthermore, it is multiplicative. The value of the Euler function is closely associated with the values of the Moebius function and the function values of the sum of the divisors of the given natural number. The Euler function is linked with systems of public key encryption. The individual values of the Euler function behave irregularly because of the irregular distribution of primes in the natural numbers. This tract is illustrated in the article with charts; summatory function for the Euler function and its average value are more predictable. We prove the formula of Martinga and, based on it, we study the approximation accuracy of the average value of the Euler function with corresponding quadratic polynomial. There is a new feature associated with the average value of the Euler function and calculate intervals of its values. We also introduce the concept of density values of the Euler function and calculate its value on the interval of the natural numbers. It can be noted that the results of the behavior of the Euler function are followed by the results in the behavior of functions of sums of divisors of natural numbers and vice versa. We have also given the results of A.Z.Valfish and A.N.Saltykov on this subject

Traditionally, control decisions are made by solving repeatedly the forecasting problem for different values of control factors and choosing a combination of them that ensures the transfer of the control object to the target state. However, real control objects are affected by hundreds or thousands of control factors, each of which can have dozens of values. A complete search of all possible combinations of values of control factors leads to the need to solve the problem of forecasting tens or hundreds of thousands or even millions of times to make a single decision, and this is completely unacceptable in practice. Therefore, we need a decision-making method that does not require significant computing resources. Thus, there is a contradiction between the actual and the desired, a contradiction between them, which is the problem to be solved in the work. In this work, we propose a developed algorithm for decision-making by solving the inverse forecasting problem once (automated SWOT analysis), using the results of cluster-constructive analysis of the target states of the control object and the values of factors and a single solution of the forecasting problem. This determines the relevance of the topic. The purpose of the work is to solve the problem. By decomposing the goal, we have formulated the following tasks, which are the stages of achieving the goal: cognitive-target structuring of the subject area; formalization of the subject area (development of classification and descriptive scales and gradations and formation of a training sample); synthesis, verification and increasing the reliability of the model of the control object; forecasting, decision-making and research of the control object by studying its model. The study uses the automated system-cognitive analysis and its software tools (the intelligent system called "Eidos") as a method for solving the set tasks. As a result of the work, we propose a developed decision-making algorithm, which is applicable in intelligent control systems. The main conclusion of the work is that the proposed approach has successfully solved the problem