No abstract

No abstract

The paper deals with developing information technology of data processing for solving business valuation problems based on the selection of comparative companies. An emerging IT company or a startup are taken as the object of study, for which traditional valuation methods are not apt. In terms of the research task there has been introduced the concept of a precedent - a company for which the search of analogues is being realized. The basic concepts of multi-agent systems are used. Four types of intelligent agents are presented that provide the implementation of the elements of the end-to-end technology: information search of objects with specified properties, intelligent processing of user requests, monitoring of objects, data mining. Stage sequence of the distributed decision-making technology has been considered. There are given metric and non-metric information processing mechanisms about analogues using metrics and proximity measures. The problem of non-metric information processing has been formulated. The tasks of data mining analysis have been defined, which are vital for monitoring the IT-companies in order to evaluate the business. The presented conclusions are summarized in the form of a complex information technology of data processing.

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

Рассмотрена задача оценки практической новизны технологий. Жизненный цикл технологии предложено рассматривать как функциональную зависимость некоторого вида, в частности полиномиальную. Предложено применение графического дифференцирования по методу хорд для нахожде-ния параметров, необходимых для оценки практической новизны технологии. Ключевые слова: практическая новизна технологии, жизненный цикл технологии, системы нечеткого вывода, алгоритм Mamdani.