High rates of the development of market relations and international integration processes imply an increase in the level of competition in leading sectors of the economy, which include energy, construction, industry enterprises and others. The purpose of this paper is to develop a universal methodology for assessing and improving the competitiveness of enterprises in the real sector of the economy. The paper analyzes the structure of cost for quality of products, examines the life cycle of the object in order to determine the approaches to the development and implementation of quality management systems. Using various methods of research, recommendations on the formation and implementation of quality management systems in enterprises of the real sector of the economy were developed in order to increase their competitiveness.
Abstract. In the article, it deals with necessity and consequences of digital economy introduction in modern society life. The strategy of the making "Digital" economy has been seen in the USA, positive and negative sides of the using different approaches of the formation "digital" economy have been analyzed, it's basic directions in Russian Federation have been represented. Based on the study of the problems and perspectives of the developing digital economy, the conclusion of the necessity to provide the assessment of the scale of the negative impacts and innovations in the possibility of the minimizing them.
The purpose of the proposed article is to study the probabilistic approach to political forecasts, obtained from experts' survey. The article describes expert information collection characteristic features, in particular, the networking: for obtaining probabilistic estimates of specialists. Especially the paper considers the different ways of interpreting these estimates. The author concludes that not only forecasting methods play an essential role in scientific forecast, (although obtained estimates values depend on the correctly chosen data and information collecting professional method), but also the obtained prognostic probabilities interpretation.
The purpose of this paper is to develop guidelines for the formation and implementation of a decision-making mechanism for managing commercial real estate. As a result of the study, the current trends in the development of the real estate market are revealed, the methods and established practice of the activities of management companies are analyzed, the analysis of theoretical approaches to the management of commercial real estate is carried out. On the basis of theoretical and methodological principles and the specifics of the analyzed area of research, methodological recommendations are proposed for the formation of a mechanism for managing commercial real estate, including a method for assessing their investment attractiveness.
The article analyzes the master plans and functional areas of 42 cities from different federal districts of the Russian Federation. To identify the dependencies between the characteristics of localities and the allocation of functional zones in them, the data clustering method was applied. Also criteria for clustering were identified – these are quantitative characteristics that are universal for various localities: total area of a locality, population, population density and gross regional product. With these criteria clustering was carried out using the software package «Deductor», based on algorithms of neural network modeling. Self-organizing Kohonen maps (SOM) were used to visualize the obtained data. As a result of the clustering the connection between the characteristics of localities and the ratio of functional zones in them is revealed.
The article analyzes the existing methods of information processing necessary for the functioning of the system of intelligent control over unregulated pedestrian crossings based on aggregation and data processing by means of IOT. The state space model of the switching Kalman filter is considered, the development of mathematical software for the analysis and processing of information based on the results of intelligent control over unregulated pedestrian crossings, in particular with semantic segmentation of trajectories using agent-based models, is carried out. An MDA (Markov Decision Process) state space model is presented, a Hidden Markov Model (HMM) which has discrete hidden variables. The developments for the development of the following subsystems are presented: activity detector subsystem. Receives video frames as input, supports the static object model (background model) and returns the hotspot mask for the current frame; subsystems for detecting and tracking objects (pedestrians and cars). Based on the video frame and hotspot mask, it detects and accompanies objects of a given class, returning their coordinates; trajectory analysis subsystem. Analyzing the history of movement of pedestrians and cars, returns the facts of traffic violations.
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