Model Oriented Decision Support System and Fuzzy Information Processing for Increasing Efficiency of University - it Company Consortia

• Autorzy: Yuriy Kondratenko , Galyna Kondratenko , Ievgen Sidenko , Vyacheslav Kharchenko
• Języki publikacji: EN

Abstrakty

EN

In the paper the existing approaches for improving abovementioned collaboration processes, technologies and methodologies based on efficient methods of optimization and decision making, modern computer-based systems and Internet opportunities are been discussed. The main contribution of the authors in this paper is a structure of computerized decision making system (CDMS) which can help partners from education and industry to find the best model of university - IT-company consortia from proposed set of efficient models A1, A2, B, C and their rational combinations.(original abstract)

Słowa kluczowe

EN

Decision making process; Computer aided decision making; Decision making; Fuzzy logic; Decision proces

PL

Proces podejmowania decyzji; Komputerowe wspomaganie decyzji; Podejmowanie decyzji; Logika rozmyta; Proces decyzyjny

• Czasopismo: Metody Ilościowe w Badaniach Ekonomicznych / Szkoła Główna Gospodarstwa Wiejskiego
• Rocznik: 2015
• Tom: 16(XVI)
• Numer: nr 1
• Strony: 157--166

Twórcy

autor

Yuriy Kondratenko

• Petro Mohyla Black Sea State University, Ukraine

autor

Galyna Kondratenko

• Petro Mohyla Black Sea State University, Ukraine

autor

Ievgen Sidenko

• Petro Mohyla Black Sea State University, Ukraine

autor

Vyacheslav Kharchenko

• National Aerospace University "KhAI", Kharkiv, Ukraine

Bibliografia

• Binderman Z., Borkowski B., Szczesny W. (2011) An Application of Radar Charts to Geometrical Measures of Structures' of Conformability, Quantitative Methods in Economics, Vol. XII, No. 1, pp. 1-13.
• Chrzanowska M., Chudzian J. (2014) Application of Regression Models in Analysis of the Advertisement's Impact on Consumer's Decision Making Process, Quantitative Methods in Economics, Vol. XV, No. 2, pp. 64-73.
• Gaspars-Wieloch H. (2014) Modifications of the Maximin Joy Criterion for Decision Making Under Uncertainty, Quantitative Methods in Economics, Vol. XV, No. 2, pp. 84-93.
• Gil-Aluja J. (1999) Investment in Uncertainty, Kluwer Academic Publishers, Dordrecht, Boston, London.
• Gil-Lafuente A. M., Merigo J. M. (2010) Decision Making Techniques in Political Management [in book] Fuzzy Optimization. Studies in Fuzziness and Soft Computing 254, Lodwick, W. A., Kacprzhyk, J. (Eds), Springer-Verlag, Berlin, Heidelberg, pp. 389-405.
• Kazymyr V. V., Sklyar V. V., Lytvyn S. V., Lytvynov V. V. (2015) Comunications Management for Academia-Industry Cooperation in IT-Engineering: Training/ V.S.Kharchenko (Ed.), Chernigiv-Kharkiv: MESU, ChNTU, NASU "KhAI".
• Kharchenko V. S., Sklyar V. V. (2014) Cooperation Between Universities and IT-Industry: Some Problems and Solutions, Kartblansh, No. 3-4, pp. 43-50.
• Kondratenko G. V., Sidenko Ie. V., Chekashova O. V. (2011) Features Synthesis of Fuzzy Hierarchical DSS in the Environment FuzzyTECH, Materials of Intern. Scientific practic. Conf. "Olvia Forum - 2011", Yalta, Ukraine, June 2011, pp. 36-36.
• Kondratenko G. V., Kondratenko Y. P., Romanov D. O. (2006) Fuzzy Models for Capacitive Vehicle Routing Problem in Uncertainty, Proc. 17th International DAAAM Symposium "Intelligent Manufacturing and Automation: Focus on Mechatronics & Robotics", Vienna, Austria, pp. 205-206.
• Kondratenko Y., Kondratenko V. (2014) Soft Computing Algorithm for Arithmetic Multiplication of Fuzzy Sets Based on Universal Analytic Models, [in book] Information and Communication Technologies in Education, Research, and Industrial Application. Communications in Computer and Information Science, Springer International Publishing Switzerland, pp. 49-77.
• Kondratenko Y., Kharchenko V. (2014) Analysis of Features of Innovative Collaboration of Academic Institutions and IT-Companies in Areas S2B and B2S, Technical news, No. 1(39), pp. 15-19.
• Kondratenko Y. P., Sidenko Ie. V. (2011) Features Synthesis and Modeling of Hierarchically-Organized DSS Based on Fuzzy Logic, Journal of the Kherson National Technical University, No, 2(41), pp. 150-158.
• Kondratenko Y. P. (2011) The Role of Inter-University Consortia for Improving Higher Education System, Proceedings of Phi Beta Delta (Ed. by Michael Smithee), Honor Society for International Scholars, USA, May 2011, Vol. 2, No. 1, рр. 26-27.
• Kondratenko Y. P., Sidenko Ie. V. (2014) Design and Reconfiguration of Intelligent Knowledge-Based System for Fuzzy Multi-Criterion Decision Making in Transport Logistics, Journal of Computational Optimization in Economics and Finance, Vol. 6, Issue 3, pp. 229-242.
• Lodwick, W. A., Kacprzhyk, J. (Eds) (2010) Fuzzy Optimization. Studies in Fuzziness and Soft Computing 254, Springer-Verlag, Berlin, Heidelberg.
• Lytvynov V. V., Kharchenko V. S., Lytvyn S. V., Saveliev M. V., Trunova E. V., Skiter I. S. (2015) Tool-Based Support of University-Industry Cooperation in IT-Engineering. Chernigiv, ChNTU.
• Rotshtein A. P. (1999) Intelligent Technologies of Identification: Fuzzy Logic, Genetic Algorithms, Neural Networks. Universum Press.
• Starov O., Sklyar V., Kharchenko V., Boyarchuk A., Phillips C. (2014) A Student-in-the- Middle Approach for Successful University and Business Cooperation in IT, Proceedings of the University-Industry Interaction Conference, Barcelona, Spain, April 2014, pp. 193-207.
• Zadeh L. A. (1965) Fuzzy sets, Information and Control, No. 8(3), pp. 338-353.