Scientific Journal of KubSAU

In this article we substantiate the necessity of the development of controlling of organizational and economic methods, including forecasting tools, the development and management of decision-making, and others. Controlling service is central to the development and implementation of organizational and economic methods to achieve the goals set by management. However, quite often the controlling service has a different name, justified by the history of the organization. To resolve this paradox, we begin with a discussion of the content of the terms "controlling" and especially "Controlling organizational and economic methods". We discuss the role of "controlling service" in the management of organizations and enterprises, as well as territorial and municipal entities. As an example of the controlling instrument of organizational and economic methods is considered an automated system of forecasting and prevention of aviation accidents, the use in this system the expert technologies and quantitative risk estimation methods. We consider this system as a controlling tool in the management of safety, while customers and performers do not use the term "controlling" in the official documentation of this project. In accordance with the Presidential Decree of 21 August 2012 № 1199 one of the 11 integrated indicators of the executive power is the indicator "estimate the population of the executive authorities." Its use in controlling in the field of strategic management of regional and municipal entities was proposed to carry out on the basis of solidary information economy (the former name - the informal information economy of the future), developed by us from 2007. We give the basic ideas of solidary information economy. However, the term "controlling" is not always used in relation to this subject. The same applies to researches related to organizational and economic modeling of innovation and development of innovative systems

In the article we have analyzed the way of scientific and technical ideas creation to mass production. Particular attention is paid to the organization of commercialization of innovative projects using modern information technologies, especially Internet auctions. To adequately describe the actual processes, we have highlighted 13 stages in the development of the innovative project and put into consideration the diversity of its trajectories. We have also identified the need for specialized structures (innovation centers), providing organizational-economic support to innovative projects, especially in the organization of expert estimates, conducting market research, developing business plans

We discuss the reasons for the development of organizational-economic support (OES) in the rocket and space industry (RSI). We have also considered the problems of estimation of the effectiveness of innovation-investment projects and ECO project management to create the rocket and space technics. On the basis of the analysis of the state and prospects of development we have developed the proposals for OES of innovation in RSI

We have allocated the basic sources of uncertainty in various industrial and economic situations. We have also considered the role and the tasks of forecasting in the management of industrial companies, particularly in the rocket and space industry. We have discussed the methods of organizational and economic forecasting - statistical, expert, combined, including foresight and given some suggestions for improving the forecasting and planning mechanisms for practical use when creating space systems

Inexpediency of use of probability of correct diagnostics as a quality indicator of diagnostic algorithm is shown. The new indicator - the prognostic strength based on Mahalanobis distance between classes is offered and studied. We have found asymptotic distribution of the prognostic strength; the way of testing of adequacy of its application has been specified. In a problem of testing of two simple hypotheses the prognostic strength connection is established with Hellinger distance

When solving some problems of economics and management at an enterprise, it becomes necessary to determine the retail price of a product or service at a known wholesale price or producer price. We offer to determine the retail price based on an analysis of a survey of potential consumers about the maximum possible price for the product or service in question. We calculate the retail price on the basis of optimizing the economic effect equal to the product of the result from the sale of one unit of goods by the demand function, which we estimate by interviewing consumers. To solve the optimization problem, we approximate the demand function using the least squares method. As examples, the linear and power models of the demand function are analyzed. Ways of further development of the proposed approach are discussed. Unresolved scientific problems are formulated. Methods for estimating the demand function in the context of a large number of repetitions of respondents and their tendency to “round numbers” require further elaboration, as a result of which the Kolmogorov criterion cannot be used to determine the accuracy of the restoration of the demand function. Various parametric and non-parametric approaches of regression analysis should be adapted to the problem of restoring the dependence of demand on price, as well as methods for solving the corresponding optimization problems

We analyze the probabilistic-statistical methods in the researches of Boris Vladimirovich Gnedenko – the academician of Ukrainian Academy of Science, which are very important for the XXI century. We have also discussed the limit theorems of probability theory, mathematical statistics, reliability theory, statistical methods of quality control and queuing theory. We give some information about the main stages of scientific career of B.V. Gnedenko, his views on the history of mathematics and teaching

From a modern point of view we have discussed Kolmogorov’s researches in the axiomatic approach to probability theory, the goodness-of-fit test of the empirical distribution with theoretical, properties of the median estimates as a distribution center, the effect of "swelling" of the correlation coefficient, the theory of averages, the statistical theory of crystallization of metals, the least squares method, the properties of sums of a random number of random variables, statistical control, unbiased estimates, axiomatic conclusion of logarithmic normal distribution in crushing, the methods of detecting differences in the weather-type experiments

The movements of electric locomotives create the interferences affecting the wired link. The creation of sufficiently technical effective and at the same time cost-effective means of protection from wireline interferences generated traction networks assumes as a preparatory phase to develop mathematical models of interference caused by electric locomotives. We have developed a probabilistic-statistical model of interferences caused by electric locomotives. The asymptotic distribution of the total interference is the distribution of the length of the two-dimensional random vector whose coordinates - independent normally distributed random variables with mean 0 and variance 1. Limit theorem is proved for the expectation of the total amplitude of the interferences. Monte-Carlo method is used to study the rate of convergence of the expectation of the total amplitude of the interferences to the limiting value. We used an algorithm of mixing developed by MacLaren-Marsaglia (M-algorithm). Five sets of amplitudes are analyzed, selected in accordance with the recommendations of experts in the field of traction AC networks. The most rapid convergence to the limit takes place in the case of equal amplitudes. It was found that the maximum possible average value of the amplitude of the random noise by 7.4% less than the previously used value, which promises a significant economic impact

The statistics of objects of non-numerical nature (statistics of non-numerical objects, non-numerical data statistics, non-numeric statistics) is the area of mathematical statistics, devoted to the analysis methods of non-numeric data. Basis of applying the results of mathematical statistics are probabilistic-statistical models of real phenomena and processes, the most important (and often only) which are models for obtaining data. The simplest example of a model for obtaining data is the model of the sample as a set of independent identically distributed random variables. In this article we have considered the basic probabilistic models for obtaining non-numeric data. Namely, the models of dichotomous data, results of paired comparisons, binary relations, ranks, the objects of general nature. We have discussed the various options of probabilistic models and their practical use. For example, the basic probabilistic model of dichotomous data - Bernoulli vector (Lucian) i.e. final sequence of independent Bernoulli trials, for which the probabilities of success may be different. The mathematical tools of solutions of various statistical problems associated with the Bernoulli vectors are useful for the analysis of random tolerances; random sets with independent elements; in processing the results of independent pairwise comparisons; statistical methods for analyzing the accuracy and stability of technological processes; in the analysis and synthesis of statistical quality control plans (for dichotomous characteristics); the processing of marketing and sociological questionnaires (with closed questions like "yes" - "no"); the processing of socio-psychological and medical data, in particular, the responses to psychological tests such as MMPI (used in particular in the problems of human resource management), and analysis of topographic maps (used for the analysis and prediction of the affected areas for technological disasters, distributing corrosion, propagation environmentally harmful pollutants, various diseases (including myocardial infarction), in other situations), etc.