Abstract
The objective of this paper is to determine a predictive model that uses the harmony search algorithm (HSA) based on available the multi-regression equation. The model employs the least squares method to predict the number of potholes in the Seoul metropolitan area. Independent variables were determined, based on traffic and weather data for each month in Seoul. Prior to the development of predictive models, empirical and stochastic factors that affect the occurrence of potholes were determined, resulting in a standardized regression coefficient from multi-linear regression analysis. A best-fit equation was derived from experiments using independent variables obtained from empirical and analytical approaches. The empirically and analytically filtered factors for each road management area in Seoul were used to develop the predictive models for the multiple regression analysis and the HSA. Fourteen predictive models were determined in this study. A performance comparison between these predictive models was conducted using the P-value, the root mean squared error, and the coefficient of determination.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Alia, O. M., Mandava, R., and Ramachandram, D. (2009) “Harmony search-based cluster initialization for fuzzy c-means segmentation of MR images.” TENCOM 2009 Conference Proceedings, DOI: 10.1109/TENCON.2009.5396049.
Kim, D., Lee, S., and Kim, D. (2014). “A predictive model for the number of potholes using basic harmony search algorithm.” Korea Journal of Construction Engineering and Management, Vol. 15, No. 4, pp. 150–158.
Ibtissem, B. and Hadria, F. (2013). “Unsupervised clustering of images using harmony searching algorithm.” Journal of Computer Science and Applications, Vol. 1, No. 5, pp. 91–99, DOI: 10.12691/jcsa-1-5-3.
Jog, G., Koch, C., Golparvar-Fard, M., and Brilakis, I. (2012). “Pothole properties measurement through visual 2D recognition and 3D reconstruction.” Computing in Civil Engineering, Proceedings, pp. 553–560, DOI: 10.1061/9780784412343.0070.
Lee, K. and Geem, Z-W. (2004a). “A new structural optimization method based on the harmony search algorithm.” Computers & Structures, Vol. 82, Nos. 9-10, pp. 781.798, DOI: 10.1016/j.compstruc.2004. 01.002.
Lee, K. S. and Geem, Z-W. (2004b). “A new meta-heuristic algorithm for continuous engineering optimization: Harmony search theory and practice.” Computer Methods in Applied Mechanics and Engineering, Vol. 194, No. 36-38, pp. 3902.3933, DOI: 10.1016/ j.cma.2004.09.007.
Lee, C-J., Kim, D-W., Mun, S., and Yoo, P-J. (2012). “Study on a prediction model of the tensile strain related to the fatigue cracking performance of asphalt concrete pavements through design of experiments and harmony search algorithm.” Journal of Korean Society of Road Engineering, Vol. 14, No. 2, pp. 11–17, DOI: 10.7855/IJHE.2012.14.2.011.
Lee, S. and Mun, S. (2014). “Improving a model for the dynamic modulus of asphalt using the modified harmony search algorithm.” Expert Systems with Applications. Vol. 41, No. 8, pp. 3856–3860, DOI: 10.1016/j.eswa.2013.12.021.
Mun, S. and Geem, Z-W. (2009a). “Determination of individual sound power levels of noise sources using a harmony search algorithm.” International Journal of Industrial Ergonomics, Vol. 39, No. 2, pp. 366–370, DOI: 10.1016/j.ergon.2008.11.001.
Mun, S. and Geem, Z-W. (2009b). “Determination of viscoelastic and damage properties of hot mix asphalt concrete using a harmony search algorithm.” Mechanics of Materials, Vol. 41, No. 3, pp. 339–353, DOI: 10.1016/j.mechmat.2008.11.008.
Mun, S. and Lee, S. (2011). “Identification of viscoelastic functions for hot-mix asphalt mixtures using a modified harmony search algorithm.” Journal of Computing in Civil Engineering, Vol. 25, No. 2, pp. 139–148, DOI: 10.1061/(ASCE)CP.1943-5487.0000078.
Mun, S. and Cho, Y-H. (2012). “Modified harmony search optimization for constrained design problems.” Expert Systems with Applications, Vol. 39, No. 1, pp. 419–423, DOI: 10.1016/j.eswa.2011.07.031.
Petroutsatou, C., Lambropoulos, S., and Pantouvakis, J-P. (2006). “Road tunnel early cost estimates using multiple regression analysis.” Operational Research. An International Journal, Vol. 6, No. 3, pp. 311–322, DOI: 10.1007/BF02941259.
Suh, Y., Mun, S., and Yeo, I. (2010). “Fatigue life prediction of asphalt concrete pavement using a harmony search algorithm.” KSCE Jounal of Civil Engineering, Vol. 14, No. 5, pp. 725–730, DOI: 10.1007/s12205-010-0906-x.
Tighe, S., Li, N., Falls, L. C., and Haas, R. (2000). “Incorporating road safety into pavement management.” Journal of the Transportation Research Board, Vol. 1699, pp. 1–10, DOI: 10.3141/1699-01.
Yang, C. (2014). “The high cost of New York’s broken roads.” Epoch Times, February 27, 2014.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Lee, S., Kim, D. & Mun, S. Development of estimated models of the number of potholes with the statistical optimization method. KSCE J Civ Eng 21, 2683–2694 (2017). https://doi.org/10.1007/s12205-017-1087-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12205-017-1087-7