An adaptive algorithm for performance assessment of construction project management with respect to resilience engineering and job security

Abstract

Construction sites are accident-prone locations and therefore safety management plays an important role in these workplaces. This study presents an adaptive algorithm for performance assessment of project management with respect to resilience engineering and job security in a large construction site. The required data are collected using questionnaires in a large construction site. The presented algorithm is composed of radial basis function (RBF), artificial neural networks multi-layer perceptron (ANN-MLP), and statistical tests. The results indicate that preparedness, fault-tolerance, and flexibility are the most effective factors on overall efficiency. Moreover, job security and resilience engineering have similar statistical impacts on overall system efficiency. The results are verified and validated by the proposed algorithm. 2018 Growing Science