UK Partner
Alexander Gegov, Reader in Computational Intelligence, School of Computing, University of Portsmouth
Ukraine Partner
Zoia Sokolovska, Head of Department, Faculty of Economic Cybernetics and Information Technologies, Odesa National Polytechnic University
Co-Investigators
Oleksii Dudnyk, Student, Faculty of Economic Cybernetics and Information Technologies, Odesa National Polytechnic University
Name Farzad Arabikhan, Senior Lecturer, School of Computing, University of Portsmouth
Project objectives
IT industry in Ukraine is relatively young but it has become an important element in creating a positive image for the country. At the end of 2021, this industry provided $6.8 billion in revenues to the Ukrainian economy and IT services exports share amounted to about 2.7% of country's GDP. The IT industry influence growth continued until the war outbreak and in February 2022 reached a record monthly export figure of $839 million. In March 2022, the Ukrainian IT industry lost 35% of the computer services exports volume, namely $317 million, compared with exports in February 2022. Expert systems can be used as a predictive tool in decision-making under uncertainty at all levels of IT industry management, e.g. at macro level, in activities of institutions whose competence includes the development of the IT industry, and at micro level, in strategic planning for the development of specific IT clusters, individual IT companies or their professional associations.
Regular monitoring and forecasting of IT industry development trends will contribute to the development of effective solutions aimed at the development of the internal IT market, directing financial flows within the economy and increasing the share of IT sector in the country's GDP.
Project goals
The aim of this research is to develop a methodology for analysing and predicting the state and dynamics of the product/outsourcing components of the country's IT industry using fuzzy logic. This will make it possible to create a system for early response to crisis phenomena and non-standard situations in the processes of the industry's operation that provides a basis for supporting relevant management decisions.
To achieve this aim, the following objectives are planned:
− to identify key factors influencing the state and dynamics of development of the product and outsourcing components of the IT industry based on an analysis of current trends in the IT industry;
− to determine the conceptual framework for the use of a fuzzy expert system as a research software platform, in particular, to propose the structure of the knowledge base;
− to test the technology of using a fuzzy expert system to predict the state and development trends of the product and outsourcing components of the IT industry in Ukraine;
− to compare the technology of using a fuzzy expert system to predict the state and development trends of the product and outsourcing components of the IT industry in the Netherlands and/or the UK.
As applied software implementation of the mathematical foundations of fuzzy logic, a novel research approach is proposed – a FuzzyKIDE fuzzy expert system. The system has been successfully tested for outsourcing IT projects portfolio management.
The architectural and technological generalisation of the developed software platform and its effective inference mechanisms provide a capability for solving a wide range of problems that arise in uncertain working conditions caused by inaccuracy in the data.
Role of each Partner.
Alexander Gegov: collaborative work on theoretical aspects of the research and the publication materials.
Zoia Sokolovska: statistical analysis of IT industries in various countries, comparative analysis of collected statistical data, editing materials for publications.
Oleksii Dudnyk: statistical analysis of IT industries in various countries, comparative analysis of the collected statistical data, collection and design of materials for publications, development of a knowledge base for the experiment, conducting an experiment using the FuzzyKIDE fuzzy expert system.
Farzad Arabikhan: collaborative work on applied aspects of the research and the publication materials.
Timing
Project Start Date: 1 February 2023
Project End Date: 31 August 2023
Expected results
1. Presentation of a joint research paper at the IEEE Conference on Artificial Intelligence.
https://cai.ieee.org/2023/
2. Publication of a joint research article in the IEEE Transactions on Artificial Intelligence.
https://cis.ieee.org/publications/ieee-transactions-on-artificial-intell...
3. Dissemination of the joint research works above through the IEEE Xplore Digital Library.
https://ieeexplore.ieee.org/Xplorehelp/overview-of-ieee-xplore/about-iee...
