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Group decision support system based on Bayesian network

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
PL
System wspomagania decyzji grupowych oparty na sieci bayesowskiej
Języki publikacji
EN
Abstrakty
EN
The article examines the process of building a developed group decision support system, its analytical and informational support. Different modes of the operation of the system are described. Software implementation and practical aspects of using such a system to resolve conflicts in supporting group decision making process are proposed. The experimental results, which allowed to confirm the effectiveness of the developed system and its application for evaluation and teaching of users are presented.
PL
Artykuł analizuje proces budowy rozwiniętego systemu wspomagania decyzji grupowych, jego wsparcie analityczne i informacyjne. Opisano różne tryby działania systemu. Proponowane jest wdrożenie oprogramowania i praktyczne aspekty korzystania z takiego systemu do rozwiązywania konfliktów we wspieraniu grupowego procesu decyzyjnego. Przedstawiono wyniki eksperymentów, które pozwoliły potwierdzić skuteczność opracowanego systemu i jego zastosowania do oceny i nauczania użytkowników.
Rocznik
Strony
123--128
Opis fizyczny
Bibliogr. 28 poz., rys., wykr.
Twórcy
  • Vinnytsia National Technical University, Khmelnytsky Hwy, 95, 21021 Vinnytsia, Ukraine
  • Vinnytsia National Technical University, Khmelnytsky Hwy, 95, 21021 Vinnytsia, Ukraine
  • State University for Transport Economy and Technologies
  • Vinnytsia Cooperation Institute, Vasyl Stus Donetsk National University, Ukraine
  • Vinnitsa State Pedagogical University named after M. Kotsyubynsky
  • Politechnika Lubelska, Katedra Elektroniki i Technik Informacyjnych, ul. Nadbystrzycka 38A, 20-618 Lublin
  • nstitute of Information and Computational Technologies CS MES RK, Almaty, Kazakhstan; University of Power Engineering and Telecommunications, Almaty, Kazakhstan
  • East Kazakhstan State Technical University named after D.Serikbayev, UstKamenogorsk, Kazakhstan
Bibliografia
  • [1] Larichev O ., Decision theory and methods, Logos, (2002), 1-53
  • [2] Chernorucky I., The decision-making methods, St Petersburg, (2005), 103-314
  • [3] Peterson M., An Introduction to Decision Theory. Second Edition, Cambridge University Press, New York (2017), 1-10
  • [4] Blumin S., Shuykova I., Models and methods of decisionmaking under uncertainty, Lipetsk, LEGP, (2001), 23-85
  • [5] Mulen E., Cooperative decision-making: axioms and models, Mir, (1991), 203-464
  • [6] Kitaev N., Group expert grades, Znaniye, (1975), 20-60
  • [7] Faynzilberg L., Bayesian scheme for collective decision making in contradiction, Problems of management and informatics, (2002), No. 3, 112–122,2002
  • [8] Faynzilberg L., Learning system of collective decision making by independent experts, Operating systems and machines, (2003), 57-62
  • [9] Bhajantri L.B., Cluster based optimization of routing in distributed sensor networks using Bayesian networks with tabu search, Int. Journal of Electronics and Telecommunications, vol 60, 2(2014), 199–208
  • [10] Tanenbaum E., Van Sten M., Distributed systems: Principles and paradigms, St Petersburg, (2003), 145-313
  • [11] Petukh A., Kuzmin E., Voytko V., Katelnikov D., The modeling of local human-machine systems of collective collaboration, Universum, Vinnitsa, (2007), 100-162
  • [12] Petukh A., Kuzmin E., Voytko V., Kuzmina N., Principles of implementation of group decision-making in interactive systems of collective collaboration, New technologies, Kremenchuk, (2008), 160–166
  • [13] Petukh A., Kuzmin E., Voytko V., Bevz S., Kopolovets N., The models of group decision making modes of users in interactive system of collective collaboration, Optic-electronic informational-energetic technologies, Vinnitsa, (2007), 80-86 (in Ukrainian)
  • [14] Petukh A., Voytko V., Katelnikov D., Kopolovets N., The interface elements of collective teaching and testing system, Measuring and computing technology in technological processes, (2007), 98-106 (in Ukrainian)
  • [15] Little I., Models and managers: The concept of a decision calculus, Management science, (1970), 466–485
  • [16] Krukov S., Bayesian networks as a tool for modeling uncertainty in investment decisions, Economic bulletin of Rostov state university, (2007), 106–111,
  • [17] Barsky A., Neural networks: recognition, management, decision making, Finance and Statistics, (2004), 50-164
  • [18] Jensen F., An introduction to Bayesian networks, Aalborg. University Denmark. Springer, (1996), 29-120
  • [19] Tolpin D., Probability networks for describing knowledge. Review of ideas, Informational processes, (2007), 93–103
  • [20] Smolarz A., Lytvynenko V., Wojcik W. et al ., Multifractal spectra classification of flame luminosity waveforms, Proceedings of SPIE, vol. 1080813, 10808 (2018), 178-186.
  • [21] Ben–Gal I., Bayesian networks. Encyclopedia of statistics in quality and reliability, John Wiley & Sons, (2007), 1-6
  • [22] Petukh A., Kuzmin E., Voytko V., Kuzmina N., Automated group decision support system, Bulletin of Vinnitsa polytechnic institute, (2009), 76-79 (in Ukrainian).
  • [23] Nosova Y., Shushliapina N., Kostishyn S.V., Koval L.G., et al., The use of statistical characteristics of measured signals to increasing the reliability of the rhinomanometric diagnosis, Proc. SPIE, 10031 (2016)
  • [24] Omioitek Z., Prokop P., The construction of the feature vector in the diagnosis of sarcoidosos based on the fractal analysis of CT chest images, IAPGOS, vol. 9 (2019), No.2, 16- 23
  • [25] Semenov A.A., Semenova O.O., Voznyak O.M., Vasilevskyi O.M., Yakovlev M.Y., Routing in telecommunication networks using fuzzy logic, 17th International Conference of Young Specialists on Micro/Nanotechnologies and Electron Devices, EDM, (2016), 173-177.
  • [26] Serkova V.K., Pavlov S.V. , Romanava V.A., et all., Medical expert system for assessment of coronary heart disease destabilization based on the analysis of the level of soluble vascular adhesion molecules, Proc. SPIE 10445, (2017), 104453O.
  • [27] Pavlov S.V., Information Technology in Medical Diagnostics (red. Waldemar Wójcik, Andrzej Smolarz), CRC Press, (2017), 1-210
  • [28] Wójcik W., Pavlov S., Kalimoldayev M., Information Technology in Medical Diagnostics II.,Taylor & Francis Group, CRC Press, Balkema book, London, (2019), 1–336
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-38568996-0982-4810-9474-3d11c49d8aed
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