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dc.contributor.author De Silva, N
dc.contributor.author Ranasinghe, KAMK
dc.date.accessioned 2013-10-21T02:12:38Z
dc.date.available 2013-10-21T02:12:38Z
dc.date.issued 2011
dc.identifier.uri http://dl.lib.mrt.ac.lk/handle/123/8157
dc.description.abstract Artificial Neural ,Network (ANN) has been used for risk analysis in various applications such as civil engineering, financial, facilities management and so on. However use of ANN has become extremely difficult when the problem is complex when handling large number of variables. Ensemble network architecture is proposed to overcome such difficulty, by combing individual "expert networks " thai learn small parts of the problem. In this research, ANN was used to analyze risks in maintainability of high-rise buildings. Analysis of maintainability risks of a building involves a large number of variables as it consists with number of components such as roof facade, etc., Therefore use of a single neural network has become impossible due to small set of data from less number of high-rise buildings in Sri Lanka. Therefore, ensemble network architecture was used in this research. The results showed that ensemble network has performed well in solving complex problems (i.e. building), by decomposing the task of the problem into its sub levels (i.e. components).
dc.language en
dc.title Use of ANN in risk analysis
dc.type Conference-Abstract
dc.identifier.year 2011
dc.identifier.conference Excellence in Research, Excelling a Nation
dc.identifier.place Faculty of Engineering, University of Moratuwa
dc.identifier.pgnos 230-232
dc.identifier.proceeding 17th Annual Research Symposium on Excellence in Research, Excelling a Nation


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