Browse > Article
http://dx.doi.org/10.5762/KAIS.2015.16.5.3477

Development of Estimation Model of Construction Activity Duration Using Neural Network Theory  

Cho, Bit-Na (Department of Civil Engineering, Gyeongsang National University)
Kim, Hyeon-Seung (Department of Civil Engineering, Gyeongsang National University)
Kang, Leen-Seok (Department of Civil Engineering, Gyeongsang National University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.16, no.5, 2015 , pp. 3477-3483 More about this Journal
Abstract
A reasonable process for the activity duration estimation is required for the successful construction management because it directly affects the entire construction duration and budget. However, the activity duration is being generally estimated by the experience of the construction manager. This study suggests an estimation model of construction activity duration using neural network theory. This model estimates the activity duration by considering both the quantitative and qualitative elements, and the model is verified by a case study. Because the suggested model estimates the activity duration by a reasonable schedule plan, it is expected to reduce the error between planning duration and actual duration in a construction project.
Keywords
Activity Duration; Back-Propagation Algorithm; Neural Network;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
연도 인용수 순위
1 S. J. Kim, J. S. Lee, "An Optimal Scheduling Method Using Probability on the Estimation of Construction Duration", Korean Journal of Construction Engineering and Management, Vol.5, No.6, pp.72-79, 2004.
2 S. C. Ok, S. K. Sinha, "Construction Equipment Productivity Estimation using Artificial Neural Network Model", Construction Management and Economics, Vol.24, Issue 10, pp.1029-1044, 2006. DOI: http://dx.doi.org/10.1080/01446190600851033   DOI   ScienceOn
3 Hag-young Han. Introduction to Pattern Recognition. p.1-572, HANBIT Media, 2009.
4 Hee-Sun Jung. Rainfall Adjust and Forecasting in Seoul Using a Artificial Neural Network Technique Including a Correlation Coefficient. Master Thesis, University of Yonsei, Seoul, Korea, 2007.
5 D. C. Kwon, C. S. Lee, "The Estimation of Construction Duration for High School Buildings Based on the Actual Data", Korean Journal of Construction Engineering and Management, Vol.5, No.22, pp.138-145, 2004.
6 A. H. Boussabaine, A. P. Kaka, "A Neural Networks Approach for Cost Flow Forecasting", Construction Management & Economics, Vol.16, Issue 4, pp.471-479, 1998. DOI: http://dx.doi.org/10.1080/014461998372240   DOI
7 J. P. Woo, H. S, Cha, K. R. Kim, D. W. Shin, "A Study on Duration Calculation Method for Eco-Friendly Remodeling Demolition Work Using Productivity Analysis", Korean Journal of Construction Engineering and Management, Vol.14, No.1, pp.124-132, 2013. DOI: http://dx.doi.org/10.6106/KJCEM.2013.14.1.124   DOI
8 J. W. Shin, H. G. Ryu, H. S. Lee, M. S. Park, "Probabilistic Model to Forecast the Duration of Structural Work in High-rise Building Construction Considering Weather Elements", Journal of Architectural Institute of Korea, Vol.23, No.6, pp.123-132, 2007.
9 H. S. Lee, J. W. Shin, M. S. Park, H. G. Ryu, "Probabilistic Duration Estimation Model for High-Rise Structural Work", Journal of Construction Engineering & Management, Vol.135, Issue 12, pp.1289-1298, 2009. DOI: http://dx.doi.org/10.1061/(ASCE)CO.1943-7862.0000105   DOI   ScienceOn
10 H. D. Han, J. H. Kim, J. H. Yoon, J. W. Seo, "Road Construction Cost Estimation Model in the Planning Phase Using Artificial Neural Network", Journal of the Korean Society of Civil Engineers, Vol.31, No.6, pp.829-837, 2011.
11 W. Pewdum, T. Rujirayanyong, V. Sooksatra, "Forecasting Final Budget and Duratio of Highway Construction Projects", Engineering, Construction and Architectural Management, 16(6), pp.544-557, 2009. DOI: http://dx.doi.org/10.1108/09699980911002566   DOI