Influence of Factors Affecting the Delay in Bridge Construction Using Neural Network-Based Sensitivity Index Method
Karlo Allen R. Pieldad
a
,
Dante L. Silva
b
,
Russell L. Diona
c
,
Kevin Lawrence M. De Jesus
d
a School of Graduate Studies, Mapua University, 658 Muralla St., 1002, Intramuros, Manila, Philippines
b School of Civil, Environmental, and Geological Engineering, Mapua University, 658 Muralla St., 1002, Intramuros, Manila, Philippines
c Information and Technology Department, University of Technology and Applied Sciences, Al Khuwair, PO Box 74, Muscat, 133, Sultanate of Oman
d Department of Civil Engineering, College of Engineering, FEU Institute of Technology, P. Paredes St., 1015, Sampaloc, Manila, Philippines
Abstract: Delays in bridge construction are crucial problems that slow down the economic development in an area. In this study, an artificial neural network (ANN) model was utilized to create a model for predicting the duration delay in bridge construction projects which includes the project amount, length of bank protection, length of bridge approach slope protection, total area of bridge approach, number of item of works, number of foundations, type of foundation, number of girders, type of girder, number of lanes, number of spans, total width, total length, and type of construction as the independent variables (IV). The modeling results showed that the best performing model is the 14–14–1 network with R = 0.99406 and MAPE of 3.524%. By removing each of the parameters, the influence of the independent variables to the duration delay was determined. Using the sensitivity index method, the findings revealed that the ranking of influence of the factors (IF) to the duration delay was observed as LBASP > NS > TW > TC > NIW > LBP > PA > TABA > TL > NG > NF > NL > TG > TF with the length of bridge approach slope protection was seen to be the most influential parameter (MIP) to the duration delay.