The article is concerned with developing mathematical support and algorithms for solving the problem of economic diagnostics of enterprises. IT-companies and start-ups (IT projects) that have special characteristics during the growth period were selected as the object of research. Based on the system analysis of data domain there has been developed a system of quantitative and qualitative characteristics to identify the economic state of the IT companies and start-ups in the external and internal environment. Scales of indices of different nature have been determined. Methods to introduce order and equivalence relations for the found peer companies have been given in order to compare their proximity to the analyzed company. Metrics used for comparing the companies are considered taking into account the quantitative and qualitative characteristics. The possibilities of distributing innovative IT projects using fuzzy clustering algorithms are considered. The comparative analysis of two basic algorithms - Fuzzy Classifier Means algorithm and Gustafson - Kessel algorithm - has been given. The clustering procedure for each algorithm is shown, as well as the graphic results of their operation. There was done the clustering quality assessment using a distribution coefficient, entropy of classification, and Hie-Beni index. It has been inferred that using Gustafson - Kessel algorithm provides better results for solving the problem of splitting IT projects for their economic diagnostics

Представлена концептуальная модель системы информационно-аналитической обеспечения управления агропромышленного комплекса. Определено, что надстройкой информационно-аналитической системы является экспертная система по поддержке принятия решений. В модели выделены территориальный и отраслевой уровни. Разработана теоретико-множественная модель организационной системы управления агропромышленном комплексом региона. Показано, что организационная система управления агропромышленным комплексом формируется по функционально-иерархическому принципу, который включает в себя несколько уровней управления. Представлена многоуровневая система сбора информации, декомпозируемая по территориальному или отраслевому признакам. Рассмотрена декомпозиция глобального бизнес-процесса

The management system of agricultural consumer supply and marketing cooperatives is considered. This system is a structure containing three levels of hierarchy: the first level includes control elements; the second level contains agricultural business representatives of the middle level; the third level includes agricultural producers. The article shows that the business processes of the agricultural producer and in his interaction with customers are end-to-end. The paper describes the flows of informational and material nature from an agricultural consumer supply and marketing cooperative (an integrator farm) to a personal subsidiary plot and from a personal subsidiary plot to an agricultural consumer supply and marketing cooperative (an integrator farm). Four structural and functional models of an agricultural consumer supply and marketing cooperative are created: one which is organised on the basis of an integrator farm; one which has an associated member, that is a processing enterprise; one which includes credit or insurance agricultural consumer cooperatives; one which sells products through chain stores. The analysis of the information exchange mechanisms during the agricultural producers’ integration is carried out. Moving material and financial flows within the models are presented. It is shown that the created models are necessary for developing route maps of business processes for reporting information in business logics language.

Purpose of research is to improve software support and identify regularities in the processes of short-term forecasting of power consumption of power supply companies based on complementary integration of data mining models, system dynamics and expert systems.Methods. The principles of constructing predictive models of power consumption are given. A system analysis has been carried out and an ontological model of the subject area has been built, taking into account the technological and market environment. The classification of forecasting methods has been considered. The features of the information base for short-term forecasting, including data on actual power consumption and weather data, have been described. The requirements for software for making forecasts have been formulated. A block diagram of the system for forecasting power consumption of the market for the day ahead is built based on the complementary integration of data analysis and modeling software.Results. Scenarios for data processing in Loginom have been developed using the Arimax and Neural Network (Regression) processors to build forecasts based on actual power consumption and taking into account meteorological factors. A system dynamics simulation model that allows exploring the influence of meteorological factors (temperature, pressure, precipitation) on power consumption has been developed in Anylogic. Using Wi!Mi mivar constructor of expert systems, the task has been parametrized; indicators, relationships, rules have been set; a logical conclusion of the solution has been obtained.Conclusion. A block diagram of a system for forecasting the market's power consumption for the day ahead has been built. It is based on the analysis of retrospective information on actual power consumption and meteorological factors using data mining methods, system dynamics and expert systems applying Russian Loginom, Anylogic and Wi!Mi software tools.

The subject of the research is the process of making managerial decisions for innovative IT projects investing. The paper focuses on the new approach to decision making on investing innovative IT projects using expert survey in a fuzzy reasoning system. As input information, expert estimates of projects have been aggregated into six indicators having a linguistic description of the individual characteristics of the project type "high", "medium", and "low". The task of decision making investing has been formalized and the term-set of the output variable Des has been defined: to invest 50-75% of the project cost; to invest 20-50% of the project cost; to invest 10-20% of the project cost; to send the project for revision; to turn down investing project. The fuzzy product model of making investment management decisions has been developed; it adequately describes the process of investment management. The expediency of using constructed production model on a practical example is shown.