name
Sergeev Alexander Eduardovich
Scholastic degree
•
Academic rank
associated professor
Honorary rank
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Organization, job position
• Kuban State University
кафедра высшей алгебры и геометрии
Доцент
Research interests
теория Галуа над различными полями и её приложения (спектры многочленов, критерии нахождения групп Галуа над полями характеристики два, группы Галуа триномов, генерирующие многочлены)
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0
TOP5 co-authors
Articles count: 23
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01.00.00 Physical-mathematical sciences
DescriptionIn this article, we discuss various issues related to the formulas approximating the distribution function of prime numbers pi(x). This question has occupied many scholars, but the exact function is well approximated function pi(x) over the number of positive integers not. Based on certain hypotheses, we present a new function s(x) is very well approximated pi(x). The above article hypotheses are so important that their numerical validation and refinement for the lengths of the segments more in 1014 - one of the main areas related to the problem of approximation of the function pi(x) throughout the series of natural numbers. After analyzing the behaviors and constructs many functions, we are building the basis of the function s(x), which is well approximates the function pi(x) throughout the series of natural numbers. We also present a table of values for x, less or equal 1022 for the difference of s(x) - pi(x)
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Description
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
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Description
Sommelier evaluates the quality of wine on the basis of their subjective feelings. At the same time, what the sommelier says when evaluating wine, it is difficult or impossible to rationally understand for the uninitiated to this art. The process of assessing the quality of wine by sommelier can not be formalized and is carried out entirely at the sensual level. Sometimes, different sommeliers differently evaluate the same wine poured from the same barrel into bottles of different prestige, with stickers differing in the number of stars. This raises at least two legitimate and natural questions. The first question is whether any subjective sommelier evaluations of the quality of wine are connected with its objective physical and chemical properties? The second question arises in the case of a positive answer to the first one: is it possible to analyze the objective methods of physical and chemical properties of wine to predict its subjective assessment by various sommeliers or some "generalized sommelier", generalizing many such subjective assessments? This article is devoted to obtaining reasoned answers to these questions. The purpose of this work, which is of great scientific and practical interest, is to create a model that provides an automated assessment of the quality of wine based on the analysis of its objective physical and chemical properties, coinciding with its sommelier-evaluation. To achieve this goal, we use Automated system-cognitive analysis (ASC-analysis) and its software tools – the intelligent system called "Eidos". A detailed numerical example based on 1599 real-world examples of sommelier evaluation of wine quality with known physical and chemical properties is considered. In addition to the answer to the two questions in the article, there is a study of the created system-cognitive model