DOI: https://doi.org/10.20998/2413-3000.2019.1326.7

THE MODEL OF IT PROJECT MANAGEMENT SYSTEM BASED ON MACHINE LEARNING

Вадимович Максим Проскурін, Віктор Володимирович Морозов, Тетяна Миколаївна Шелест

Abstract


A model is proposed for integrating modern IT project management with artificial intelligence technologies, taking into account current trends and developments in the field of IT computer science and allows you to effectively handle the growing data flows on the parameters and characteristics of complex projects when developing and making decisions on managing complex projects. Identified and classified the main reasons affecting the unsuccessful completion of projects. The components of the proposed model for integrating the project management system are shown and their detailed characteristics are presented. It is determined that the proposed model is based on three components, including a list of basic methodologies and standards for project management, which can form hybrid methodologies, a set of IT, database and project management knowledge for developing, substantiating and managing projects and modern artificial technologies intelligence based on the use of machine learning methods. The role, components and environment of machine learning for use in project management is substantiated. The integration conditions were used to analyze and build a table of modern IT for project management, clustering them into three groups concerning the possibilities of using artificial intelligence technologies, in particular machine learning. The results of introducing elements of the proposed model in the implementation of complex IT projects in the banking sector have shown the effectiveness of the proposed approach. The success of current projects and portfolios of projects of the bank has increased, the number of participants in project activities working in real projects with processing large amounts of information on managing the development and implementation of complex IT products has increased.

Keywords


project management; complex IT projects; information technologies; artificial intelligence; data flows; machine learning

References


Krap N. P., Yusevich V. M. Nejronni merezhi jak zasib upravlinnja konfighuracijamy proektiv turystychnykh potokiv [Neural networks as a means for managing the configurations of tourist flows projects]. Upravlinnja rozvytkom skladnykh system [Management of the development of complex systems]. 2013, issue 14, pp. 37-40.

Nazimko V. V., Zakharova L. N. Razrabotka nejrosetevoj modeli dlja upravlenija riskami proekta [Development of neural network model for risk management of the project]. Zb. nauk. pracj “Proektno–orijentovana dijaljnistj socialjno-ekonomichnykh system: suchasnyj poghljad” [Zb. sciences Works "Project-oriented activity of socio-economic systems: modern view"]. Donetsk: DonNUU, 2010, vol. 11, no. 158, pp. 73-82.

Slya M.R. Zastosuvannja metodiv shtuchnogho intelektu dlja rozv'jazannja systemnykh zadach rozpiznavannja krytychnykh sytuacij [Application of Artificial Intelligence Methods for Solving Systemic Problems of Recognition of Critical Situations]. International scientific journal. 2016, no. 7, pp. 124-128. Available at: http://nbuv.gov.ua/UJRN/mnj_2016_7_30.

Timofeeva E.S. Udoskonalennja metodiv upravlinnja proektamy na pidpryjemstvakh ghirnycho-metalurghijnogho kompleksu za rakhunok vykorystannja mekhanizmiv shtuchnogho intelektu [Improvement of project management methods at the enterprises of the mining and metallurgical complex through the use of mechanisms of artificial intelligence]. Upravlinnja proektamy ta rozvytok vyrobnyctva: Zb.nauk.pr. [Project management and production development: Zb.nauc.pr]. Lugansk: View of the SNU them. V. Dalya, 2008, no. 3 (27), pp. 129-137. Available at: http://www.pmdp.org.ua/images/Journal/27/08tesmii.pdf.

A. Begler, T. Gavrilova. Artificial Intelligence Methods for Knowledge Management Systems. Working Paper #9 (E), 2018. Graduate School of Management, St. Petersburg University: SPb, 2018.

Nemati H. R., Steiger D., Iyer L. S., and Herschel R. T. Knowledge Warehouse: An Architectural Integration of Knowledge Management, Decision Support, Artificial Intelligence and Data Warehousing. Decision Support Systems, 2002, no. 33 (2), pp. 143-161.

Liebowitz, J. Knowledge Management and Its Link to Articial Intelligence. Expert Syst. Appl. 2001, no. 20 (1), pp. 1–6.

Kadhim, Mohammed Abbas, M. Afshar Alam, and Harleen Kaur. A Multi-Intelligent Agent Architecture for Knowledge Extraction: Novel Approaches for Automatic Production Rules Extraction.” International Journal of Multimedia and Ubiquitous Engineering. 2014, no. 9(2), pp. 95–114. doi.org/10.14257/ijmue.2014.9.2.10.

Chang C.K., Christensen M.J., and Zhang T., Genetic algorithms for project management. Annals of Software Engineering, 2001, no. 11(1), pp. 107-139.

Kononenko I.V., Aghaee A. Model and Method for Synthesis of Project Management Methodology With Fuzzy Input Data. Bulletin of NTU" KhPI". Ser. : Strategic Management, Portfolio, Program and Project Management. 2016, no. 1 (1173), pp. 9–13. doi : 10.20998/2413-3000.2016.1173.2.

Teslya Yu. N., Kontsevich V. V. Primeneniye teorii nesilovogo vzaimodeystviya v proaktivnom upravlenii kachestvom proyekta [Application of non-force interaction theory in proactive project quality management]. Upravlіnnya rozvitkom skladnikh system [Managing the development of complex systems]. 2013, issue 13, pp 58-61.

Biloshchytskyi A., Kuchansky А., Andrashko Yu., Biloshchytska S., Kuzka О., Shabala Ye., Lyashchenko T. A method for the identification of scientists' research areas based on a cluster analysis of scientific publications. Eastern-European Journal of Enterprise Technologies. 2017, no. 5, vol. 2, issue 89, pp. 4-10. doi:10.15587/1729-4061.2017.112323.

Morozov V., Kalnichenko O., Liubyma Iu. Anticipative Approach to Project Management for the Creation of Distributed Information Systems. Proceedings of the 2018 IEEE XIII-th International Scientific and Technical Conference on COMPUTER SCIENCE AND INFORMATION TECHNOLOGIES (CSIT), Lviv Polytechnic National University, Lviv, Ukraine, September 11-14, V.2, 2018.

Nemati H.R., Steiger D., Iyer L.S., and Herschel R.T. Knowledge Warehouse: An Architectural Integration of Knowledge Management, Decision Support, Artificial Intelligence and Data Warehousing, Decision Support Systems, 2002, no. 33 (2), pp. 143-161.

Liebowitz, J. 2001. “Knowledge Management and Its Link to Articial Intelligence”. Expert Syst. Appl. No. 20 (1). pp. 1–6.

Kadhim, Mohammed Abbas, M. Afshar Alam, and Harleen Kaur. A Multi-Intelligent Agent Architecture for Knowledge Extraction: Novel Approaches for Automatic Production Rules Extraction. International Journal of Multimedia and Ubiquitous Engineering. No. 9(2). pp. 95–114. https://doi.org/10.14257/ijmue.2014.9.2.10.

Chang C.K., Christensen M.J., and Zhang T. Genetic algorithms for project management. Annals of Software Engineering, 2001, no. 11(1), pp. 107-139.

Project Smart. The Standish Group Report - Chaos Report. 2014. Available at: https://www.projectsmart.co.uk/white-papers/chaos-report.pdf.

Pulse of the profession (10th Global Project Management Survey). PMI, 2018, pp. 2325. Available at: https://www.pmi.org/-/media/pmi/documents/public/pdf/learning/thought-leadership/pulse/pulse-of-the-profession-2018.pdf.

Vegard K., Richard A., Robert J. T. How Artificial Intelligence Will Redefine Management. Harvard Business Review. 2016. Available at: https://hbr.org/2016/11/how-artificial-intelligence-will-redefine-management.

Samuel, Arthur. Some Studies in Machine Learning Using the Game of Checkers. IBM Journal of Research and Development. 1959, no. 3 (3), pp. 210–229. doi:10.1147/rd.33.0210.

Artificial Intelligence Market by Offering, Technology, End-User Industry And Geography - Global Forecast to 2025. Available at: https://www.reportbuyer.com/product/4412107/artificial-intelligence-market-by-offering-technology-end-user-industry-and-geography-global-forecast-to-2025.html.

Aurora. Available at: www.stottlerhenke.com/products/aurora/

Forecast. Available at: https://www.forecast.app/

ClickUp. Available at: https://clickup.com/

Riter AI. Available at: https://riter.co/

Lili.ai. Available at: http://lili.ai/

Rescoper. Available at: https://rescoper.com/

New Relic. Available at: https://newrelic.com/

Teodesk. Available at: https://www.teodesk.com/

Aptage. Available at: https://get.aptage.com/rbd/

ProjectHealth. Available at: https://labs.eleks.com/

Harmon.ie. Available at: https://harmon.ie

Stratejos. Available at: https://stratejos.ai/

OneBar. Available at: https://onebar.io/

Fireflies.ai. Available at: https://fireflies.ai/

Dialogflow. Available at: https://dialogflow.com/


GOST Style Citations


1. Крап Н. П., Юзевич В. М. Нейронні мережі як засіб управління конфігураціями проектів туристичних потоків. Управління розвитком складних систем. 2013. Вип. 14. С. 37–40.


2. Назимко В. В., Захарова Л. Н. Разработка нейросетевой модели для управления рисками проекта. Зб. наук. праць “Проектно–орієнтована діяльність соціально-економічних систем: сучасний погляд”. Донецьк: ДонДУУ, 2010. Т. 11, № 158. С. 73-82.


3. Сльота М. Р. Застосування методів штучного інтелекту для розв’язання системних задач розпізнавання критичних ситуацій. International scientific journal. 2016. № 7. С. 124-128. URL: ttp://nbuv.gov.ua/UJRN/mnj_2016_7_30.


4. Тимофієва Є.С. Удосконалення методів управління проектами на підприємствах гірничо-металургійного комплексу за рахунок використання механізмів штучного інтелекту. Управління проектами та розвиток виробництва: Зб.наук.пр. Луганськ: вид-во СНУ ім. В.Даля, 2008. № 3 (27). С. 129-137. URL: http://www.pmdp.org.ua/images/Journal/27/08tesmii.pdf.


5. A. Begler, T. Gavrilova. Artificial Intelligence Methods for Knowledge Management Systems. Working Paper #9 (E). Graduate School of Management, St. Petersburg University: SPb, 2018.


6. Nemati H. R., Steiger D., Iyer L. S., and Herschel R. T. Knowledge Warehouse: An Architectural Integration of Knowledge Management, Decision Support, Artificial Intelligence and Data Warehousing. Decision Support Systems, 2002. No. 33 (2), P. 143-161.


7. Liebowitz, J. Knowledge Management and Its Link to Articial Intelligence. Expert Syst. Appl. 2001. No. 20 (1). P. 1–6.


8. Kadhim, Mohammed Abbas, M. Afshar Alam, and Harleen Kaur. A Multi-Intelligent Agent Architecture for Knowledge Extraction: Novel Approaches for Automatic Production Rules Extraction.” International Journal of Multimedia and Ubiquitous Engineering. 2014, No. 9(2). pp. 95–114. doi.org/10.14257/ijmue.2014.9.2.10.


9. Chang C.K., Christensen M.J., and Zhang T., Genetic algorithms for project management. Annals of Software Engineering, 2001. No. 11(1). P. 107-139.


10. Kononenko I.V., Aghaee A. Model and Method for Synthesis of Project Management Methodology With Fuzzy Input Data. Bulletin of NTU" KhPI". Ser. : Strategic Management, Portfolio, Program and Project Management. 2016. no. 1 (1173). pp. 9–13. doi : 10.20998/2413-3000.2016.1173.2.


11. Тесля Ю. Н., Концевич В. В. Применение теории несилового взаимодействия в проактивном управлении качеством проекта. Управління розвитком складних систем. 2013. Вип. 13. С. 58-61.


12. Biloshchytskyi A., Kuchansky А., Andrashko Yu., Biloshchytska S., Kuzka О., Shabala Ye., Lyashchenko T. A method for the identification of scientists' research areas based on a cluster analysis of scientific publications. Eastern-European Journal of Enterprise Technologies. 2017. No. 5. Vol. 2. Issue 89. Р. 4-10. doi:10.15587/1729-4061.2017.112323.


13. Morozov V., Kalnichenko O., Liubyma Iu. Anticipative Approach to Project Management for the Creation of Distributed Information Systems. Proceedings of the 2018 IEEE XIII-th International Scientific and Technical Conference on COMPUTER SCIENCE AND INFORMATION TECHNOLOGIES (CSIT), Lviv Polytechnic National University, Lviv, Ukraine, September 11-14, V.2, 2018.


14. Nemati H.R., Steiger D., Iyer L.S., and Herschel R.T. Knowledge Warehouse: An Architectural Integration of Knowledge Management, Decision Support, Artificial Intelligence and Data Warehousing, Decision Support Systems, 2002. No. 33 (2). P. 143-161.


15. Liebowitz, J. 2001. “Knowledge Management and Its Link to Articial Intelligence”. Expert Syst. Appl. No. 20 (1). P. 1–6.


16. Kadhim, Mohammed Abbas, M. Afshar Alam, and Harleen Kaur. A Multi-Intelligent Agent Architecture for Knowledge Extraction: Novel Approaches for Automatic Production Rules Extraction. International Journal of Multimedia and Ubiquitous Engineering. No. 9(2). pp. 95–114. https://doi.org/10.14257/ijmue.2014.9.2.10.


17. Chang C.K., Christensen M.J., and Zhang T. Genetic algorithms for project management. Annals of Software Engineering, 2001. No. 11(1). P. 107-139.


18. Project Smart. The Standish Group Report - Chaos Report. 2014. URL: https://www.projectsmart.co.uk/white-papers/chaos-report.pdf.


19. Pulse of the profession (10th Global Project Management Survey). PMI, 2018. P. 23-25. URL: https://www.pmi.org/-/media/pmi/documents/public/pdf/learning/thought-leadership/pulse/pulse-of-the-profession-2018.pdf.


20. Vegard K., Richard A., Robert J. T. How Artificial Intelligence Will Redefine Management. Harvard Business Review. 2016. URL: https://hbr.org/2016/11/how-artificial-intelligence-will-redefine-management.


21. Samuel, Arthur. Some Studies in Machine Learning Using the Game of Checkers. IBM Journal of Research and Development. 1959. No. 3 (3). P. 210–229. doi:10.1147/rd.33.0210.


22. Artificial Intelligence Market by Offering, Technology, End-User Industry And Geography - Global Forecast to 2025. URL: https://www.reportbuyer.com/product/4412107/artificial-intelligence-market-by-offering-technology-end-user-industry-and-geography-global-forecast-to-2025.html.

23. Aurora. URL: https://www.stottlerhenke.com/products/aurora/


24. Forecast. URL: https://www.forecast.app/


25. ClickUp. URL: https://clickup.com/


26. Riter AI. URL: https://riter.co/


27. Lili.ai. URL: http://lili.ai/


28. Rescoper. URL: https://rescoper.com/


29. New Relic. URL: https://newrelic.com/


30. Teodesk. URL: https://www.teodesk.com/


31. Aptage. URL: https://get.aptage.com/rbd/


32. ProjectHealth. URL: https://labs.eleks.com/


33. Harmon.ie. URL: https://harmon.ie/


34. Stratejos. URL: https://stratejos.ai/


35. OneBar. URL: https://onebar.io/


36. Fireflies.ai. URL: https://fireflies.ai/


37. Dialogflow. URL: https://dialogflow.com.







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