Proceedings of the 2021 European Conference on Computing in Construction

     

Using Artificial Neural Networks to Model Bricklaying Productivity

Orsolya Bokor, Laura Florez,Perez, Giovanni Pesce, Nima Gerami Seresht
1: Northumbria University, United Kingdom
2: University College London, United Kingdom


DOI: 10.35490/EC3.2021.155
Abstract: The pre-planning phase prior to construction is crucial for ensuring an effective and efficient project delivery. Realistic productivity rates forecasted during pre-planning are essential for accurate schedules, cost calculation, and resource allocation. To obtain such productivity rates, the relationships between various factors and productivity need to be understood. Artificial neural networks (ANNs) are suitable for modelling these complex interactions typical of construction activities, and can be used to assist project managers to produce suitable solutions for estimating productivity. This paper presents the steps of determining the network configurations of an ANN model for bricklaying productivity.
Keywords: Temporary Objects, Point cloud segmentation, Construction monitoring, TLS, Large point cloud
Pages: 52 - 58
Paper:
EC32021_155

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