Chernov Sergiy, Gaida Anatoly , Kharitonov Yuriy , Koshkin Volodymyr
Дата публікації:


Анотація (укр):

Запропоновано організаційну структуру системи підтримки прийняття рішень проектів реконструкції систем водопостачання. Для вибору раціонального проекту використано механізм нейронних мереж. Виконано апробацію системи.

Анотація (рус):

Предложена организационная структура системы поддержки принятия решений проектов реконструкции систем водоснабжения. Для выбора рационального проекта используется механизм нейронных сетей. Проведена апробация системы.

Анотація (англ):

Current conditions of most project-oriented businesses based activities are related to the implementation of projects requires the management of these companies develop and apply appropriate procedures, methods and management techniques. The complexity of using classical approaches arises from the fact that the activities of design organizations is in many ways a unique non-recurring process. The practice of these companies shows that much attention from their owners paid not only to the global strategic objectives, but the current results of operations. In real situations, work portfolio management takes place in a high degree of uncertainty: the time of admission of projects, time and costs of their implementation, as well as other factors are random variables with specified or unknown distribution laws. On the basis of the standard portfolio management Project Management Institute USA (PMI) analyzed the portfolio management process using Markov chains for discrete states of the system. Identified processes (state) in which the portfolio manager is busy most of the time. Markov model state changes to determine the loading of a portfolio manager at various stages of portfolio management, which makes it possible to use these data in determining the KPI project managers when evaluating their work.



  1. Barsky, A.B. (2007). LogicNeural Networks: A Tutorial [Text] /A.B.Barsky- M.: Internet Univ Inf.Tehnol. -INTUIT. Roux. Moscow, Russia: BINOM, Lab.knowledge, 352.
  2. Kovalenko, I.I. (2013). Expert technologies for decision support [Text] / I.I. Kovalenko, A.V. Shved. Nikolayev, Ukraine: Ilion, 216.
  3. Kovalenko, I.I. (2014). Some Principles of Creation of Decision Making Support System in Projects of Reconstruction of Municipal systems of water-supply [Text]/ I.I. Kovalenko, V.K. Koshkin // Management of development of complex system. Kyiv, Ukraine: KNUBA, 67-71
  4. Mikhalenko, V.M. (2012). Informational-analytical system architecture of development and reconstruction project of municipal water supply system of the city [Text]/ V.M. Mikhalenko, O.L Solovey // Project management and production development, 1 (41),  1-5.
  5. National Report: The qualityof drinkingwater and the situationof drinking water in Ukraine in 2011[electronic resource] http://minregion.gov.ua/attachments/files/zhkh/Vodopostachannya/ – TitleScreen.
  6. Haykin, S. (2006). Neural Networks. Full course[Text] /S.Haykin//-2nd ed., Rev.:Trans.Translated from English. Moscow, Russia: LLC "I. D. Williams", 1104 P.
  7. Koshkin, V. (2014). Water resouces decision support system [Text] V. Koshkin//National Scientific andPractical Internet Conference: Principles and Mechanisms. Donetsk, Ukraine: 87-90.
  8. Optimal Design of Water Distribution System by Multiobjective Evolutionary Methods Klebber T. M. Formiga1, Fazal H. Chaudhry1, Peter B. Cheung1, Luisa F. R. Reis [Electronic resource] http://www.bwd.com.br/ geasd/fotos/gea publicacoes1.pdf– TitleScreen.
  9. Water distribution system design guindelines and standard specifications and details. http://dpuserver.drivehq.com/waterdistributionuqui delines_specifications.pdf.