Year 2016

• Prototyp modelu systemu samouczącego do prognozowania stężenia pyłu PM10 w powietrzu atmosferycznym

  Publication

  • C. Orłowski
  • A. Sarzyński
  • M. Sarzyńska

  - Year 2016

  Artykuł przedstawia model prognozowania stężenia pyłu PM10 z wykorzystaniem algorytmów genetycznych. Model ten jest drugim z kolei do prognozowania pyłu (poprzedni wykorzystywał jednokierunkowe sieci neuronowe) i stanowi podstawę do budowy modelu samouczącego. Podczas budowy modelu uwzględniono oddziaływanie czynników meteorologicznych, a do implementacji wykorzystano algorytm genetyczny ze względu na specyfikę problemu prognozowania...

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Year 2015

• Experience-Driven Model of Decision-Making Processes in Project Teams

  Publication

  • C. Orłowski
  • A. Sarzyński
  • T. Sitek
  • A. Ziółkowski

  - CYBERNETICS AND SYSTEMS - Year 2015

  This article presents a model of decision-making processes in project teams. Project teams constitute a specific type of organization appointed to implement a project. Decisions made by project teams result from the methods of project management and best management practices. The authors have undertaken the task of formalizing these processes using the classical method of constructing decision trees. It has been established that...

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Year 2014

• A MODEL FOR FORECASTING PM10 LEVELS WITH THE USE OF ARTIFICIAL NEURAL NETWORKS

  Publication

  • A. Sarzyński
  • C. Orłowski

  - Year 2014

  This work presents a method of forecasting the level of PM10 with the use of artificial neural networks. Current level of particulate matter and meteorological data was taken into account in the construction of the model (checked the correlation of each variable and the future level of PM10), and unidirectional networks were used to implement it due to their ease of learning. Then, the configuration of the network (built on the...

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