THE METHOD OF INTERACTION MODELING ON BASIS OF DEEP LEARNING THE NEURAL NETWORKS IN COMPLEX IT-PROJECTS

Authors

  • Viktor V. Morozov
  • Olena V. Kalnichenko
  • Olga Olga O. Mezentseva Mezentseva

Keywords:

cloud technologies, distributed information systems, IT-projects, project management, proactive management, information impacts, influences, interaction, change management.

Abstract

In this paper, we propose a method for using neural networks to model impacts on the parameters of complex IT projects for the creation of distributed information systems. The method allows predicting the level of changes in the results of the project activity at any time during the execution of projects and depending on changes in the time parameters of projects. An integrated information system is developed for modelling the changes of key parameters of IT projects using cloud data warehouses. The modern information technologies of management projects of leading developers are involved and integrated in the process of modelling. The evaluation of the results of modelling the effects of changes on the timing of work implementation is carried out taking into account the context characteristics of projects, including resource distribution both in time and in project work, cost distribution, etc. The model of in-depth training of the neural network is proposed, due to the experimental representation of the input and output data of numerical experiments. In this paper we propose a method for analysing the effects of changes on the terms of project execution.

References

Trends in the Development of the Global Market for Information Technology. [Online]. Available at: http://eir.pstu.edu/handle/123456789/4299.

Cloud Terminology – Key Definitions, 2007, [Online]. Available at: https://www.Getfilecloud.com/cloud-terminology-glossary/.

Cloud Computing and Emerging IT Platforms: Vision, Hype, and Reality for Delivering Computing as the 5th Utility, [Online]. Available at: http://www.sciencedirect.com/science/article/pii/S0167739X08001957.

B. Furht, A. Escalante, Handbook of Cloud Computing, [Online]. Available at: https://link.springer.com/book/10.1007/978-1-4419-6524-0.

O. Maimon, L. Rokach, Data Mining and Knowledge Discovery Handbook, 2005, [Online]. Available at: http://www.bookmetrix.com/detail/book/ae1ad394-f821-4df2-9cc4-cbf8b93edf40.

Proactive Project Management, [Online]. Available at: http://www.itexpert.ru/rus/ITEMS/200810062247/

International Project Management Association. Individual Competence Baseline Version 4.0. International Project Management Association, 2015, 432 p.

A Guide to the Project Management Body of Knowledge (PMBoK Guide), Sixth Edition, PMI Inc., 2017, 537 p.

R. Evaristo, “The management of distributed projects across cultures,” Journal of Global Information Management (JGIM), vol. 11, issue 4, pp. 58-70, 2003.

M. Zieja, H. Smoliński, P. Gołda, “Proactive methods – new quality in aircraft flight safety management”, 2015, [Online]. Available at: https://www.degruyter.com/downloadpdf/j/jok.2015.36.issue-1/jok-2015-0060/jok-2015-0060.pdf

V. Gogunskiy, K. Kolesnikova, D. Lukianov, “Lifelong learning is a new paradigm of personnel training in enterprises,” Eastern-European Journal of Enterprise Technologies, no. 4/2 (82), pp. 4–10, 2016.

O. Dunets, C. Wolff, A. Sachenko, G. Hladiy, I. Dobrotvor “Multi-agent System of IT Project Planning”, in Proceedings of the 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), Bucharest, 21-23 September 2017, vol. 2, pp. 548-553.

V. Morozov, O. Kalnichenko, S. Bronin “Development of the model of the proactive approach in creation of distributed information systems,” Eastern-European Journal of Enterprise Technologies, no. 43/2 (94), pp. 6-15, 2018.

V. Morozov, O. Kalnichenko, M. Proskurin, O. Mezentseva, “Investigation of forecasting methods the state of complex IT-projects with using deep learning neural networks,” in the book “Lecture Notes in Computational Intelligence and Decision Making” (series “Advances in Intelligent Systems and Computing”), vol. 1020, pp. 261-280, 2020.

F. Fabiano, L. Pugliese, F. Guerriero, “The project management in Italian air force and the Touch&Go methodology,” Proceedings of the 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS’2019, Metz, France, 18-21 September 2019, pp. 730-735.

C. Cruz, R. Marques, “Using the ‘economic and financial re-equilibrium’ model to decrease infrastructure contract incompleteness,” Journal of Infrastructure Systems, vol. 9, issue 1, pp. 58-66, 2013.

R. Turner, Guide to Project-based Management, transl. from English, Moscow: Grebennikov Publishing House, 552 p., 2007. (in Russian)

I. Prigogine, G. Nikolis, Knowledge of the Complex, transl. from English, Moscow: Lenar, 2017, 360 p.

D. Garaedagi, System Thinking. How to Manage Chaos and Complex Processes. Platform for Modeling Business Architecture, Grevtsov Publicher, 480 p., 2011.

A. Novikov, A. Ezhov, “Rosenblatt's multilayer neural network and its application for solving the problem of signature recognition,” Bulletin of TSU. Technical science, no. 2, pp. 188-197, 2016.

C. Chatfild, T. Johnson, Microsoft Project 2016 Step by Step, Amazon Digital Services LLC, 2016, 577 p.

V.I. Komashinsky, D.A. Smirnov, Neural Networks and their use in Control and Communication Systems, Moscow: Hotline-Telecom, 2003, 94 p.

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Published

2020-03-31

How to Cite

Morozov, V. V., Kalnichenko, O. V., & Mezentseva, O. O. O. M. (2020). THE METHOD OF INTERACTION MODELING ON BASIS OF DEEP LEARNING THE NEURAL NETWORKS IN COMPLEX IT-PROJECTS. International Journal of Computing, 19(1), 88-96. Retrieved from http://computingonline.net/computing/article/view/1697

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