Integration between neuro-fuzzy system and Monte Carlo simulation for duration estimation of the bored piles

Thoedtida Thipparat

International Journal of Business and Systems Research, 2013, vol. 7, issue 2, 189-207

Abstract: Traditional methods of duration prediction of the bored pile projects are far from accurate and consistent. This can be attributed to the fact that the problem in estimating the construction duration is very complex and not yet precisely understood. Neuro-fuzzy system (NFS) has been proposed to deal with several problems associated with cognitive uncertainty caused by human subjectivity. Despite the relative merits of the NFS, it cannot determine non-cognitive caused by factors such as constant change of site conditions, low technical competence of workers, material unavailability, and bad weather conditions. These factors result in the variation in activity duration. An alternative stochastic approach is necessary for providing more rational estimation of activity duration. In this paper, the probability distribution of activity duration is obtained by integrating the NFS with Monte Carlo simulation. The estimators can make a decision regarding risk factors and their impacts on the estimated duration by employing the proposed method. As a result, a more realistic estimation of the actual duration can be provided.

Keywords: adaptive neuro-fuzzy inference systems; ANFIS; Sugeno; Monte Carlo simulation; duration estimation; bored piles; neural networks; fuzzy logic; risk assessment; construction projects; operation duration; piling projects. (search for similar items in EconPapers)
Date: 2013
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