Abstract
Issues related to the development and implementation of distributed information systems, which today are the most important decision in the IT market, are considered in this article. The tendencies of negative completion of such projects are analyzed. The conclusion is made on the need to take into account the environmental impacts of such projects and the use of proactive project management technologies in these processes, which are currently quite developed and effective. Attention is paid to the development of a conceptual model for the interaction of complex IT projects with their external environment. The authors propose a model “cube of interaction processes” to determine the types of influences on the system (projects) and its reaction. The method of forecasting the status of projects from the effect of changes on the basis of impacts from the project environment is proposed. The basis of the method is the processes of deep learning of neural networks. Initiation and implementation of change management is envisaged on the basis of accumulated knowledge, principles of system analysis and mechanisms of convergence of methodologies for the creation of such systems. The mathematical description of this method is proposed in the article, which defines the interaction of elements and characteristics with the impact of changes in projects for the creation of distributed information systems. Attention is paid to the experimental study of the processes of interaction of elements of such systems with the use of modern neural networks. As variables parameters were chosen the amount of resources that are provided to the work of projects for their implementation.
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Morozov, V., Kalnichenko, O., Proskurin, M., Mezentseva, O. (2020). Investigation of Forecasting Methods of the State of Complex IT-Projects with the Use of Deep Learning Neural Networks. In: Lytvynenko, V., Babichev, S., Wójcik, W., Vynokurova, O., Vyshemyrskaya, S., Radetskaya, S. (eds) Lecture Notes in Computational Intelligence and Decision Making. ISDMCI 2019. Advances in Intelligent Systems and Computing, vol 1020. Springer, Cham. https://doi.org/10.1007/978-3-030-26474-1_19
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