Late Payments for Contractors Working for Bahrain Government Building Construction Projects: Part II (Modelling Using Artificial Neural Networks and Regression)
Journal: International Journal of Science and Research (IJSR) (Vol.7, No. 3)Publication Date: 2018-03-05
Authors : Sahar K. A. Falamarzi; Saad M. A. Suliman;
Page : 700-723
Keywords : Interim payment delay; Variation payment delay; artificial neural network; multi linear regression analysis;
Abstract
The problem of late payment is considered one of the major issues in the construction industry, it is an important issue faced by many countries including Kingdom of Bahrain, and it has many consequences on building construction projects. The main objectives of this research is to create a prediction model to predict the payment delay in days for Interim payments (Model I) and variation payments (Model V) for Ministry of Works (MoW) building construction projects. The main factors of payment delay were identified in Part I of the research and used for the development of models using artificial neural network (ANN) and multi linear regression analysis (MLRA). Finally, the study compared the ANN approach to MLRA and concluded that the estimation accuracy of ANN approach is better than MLRA analysis for payment delay in (days) as it showed more promising results. The best ANN for Model I and Model V were found to be Model I-48 and Model V-60, respectively.
Other Latest Articles
- Late Payments for Contractors Working for Bahrain Government Building Construction Projects: Part I (Factors and Consequences of Late Payment)
- Three Coupler Position Synthesis and Kinematic Analysis for a Couple of Four-Bar Mechanism
- Ergonomic Analysis of Musculoskeletal Issues in Indian Footwear Factory Workers
- A Survey of Toxic Metal Concentrations in Food Chain Level at Rajshahi District Area in Bangladesh
- Analysis of Cost Leadership Strategy and Differentiation Strategy in Creating Competitive Advantages and their Impact on Performance
Last modified: 2021-06-28 19:05:38