Latest revision as of 15:28, 17 September 2020

Abstract

Life-cycle management of urban road networks as a part of an urban system is a very complex process from the management standpoint of social, technical and economic aspects. The complexity and multidisciplinarity of such a problem suggest the need for using soft computing tools as well as multicriteria analysis and group decision-making. Recently, there is a significant increase in using various soft computing tools, especially neural networks, for different prediction purposes in the field of road construction planning and management. Along with known advantages of such a prediction method, yet some applications showed the shortcomings. In that sense, the focus of this research is on possible applications of neural networks related to the life-cycle phases during the management of urban road projects. This is done in both horizontal (projects‘ life-cycle phases) and vertical (hierarchical decisionmaking levels) approach. The final aim of the research is to compare and highlight the possible applications of neural networks as a prediction tool and support for decision-making in urban road management.

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