Open Access
MATEC Web Conf.
Volume 81, 2016
2016 5th International Conference on Transportation and Traffic Engineering (ICTTE 2016)
Article Number 07002
Number of page(s) 5
Section Construction Project Modeling and Prediction
Published online 25 October 2016
  1. I.A. Rahman, A.H. Memon, A. Azis and N. Abdullah. Modeling causes of cost overrun in large construction projects with partial least square-SEM approach: Contractor’s perspective. Engineering and Technology 5, 1963–1972, (2013).
  2. C.H. Mulder. Population and housing: A two sided relationship. Demographic Research 15, 401–412. (2006). [CrossRef]
  3. W.S Thompson. Population growth and housing demand. The ANNALS of the American Academy of Political and Social Science 190, 131–137, (1937). [CrossRef]
  4. G.E.P Box & G. Jenkins. Time series analysis, forecasting and control, Holden-Day, San Francisco, California. (1970).
  5. G.P. Zhang. Time series forecasting using a hybrid ARIMA and neural network model, Neurocomputing 50, 159–175, (2003). [CrossRef]
  6. K.K. Lai, L. Yu, S.Y. Wang and W. Huang. Hybridizing exponential smoothing and neural network for financial time series predication. Computational Science–ICCS. Springer Berlin Heidelberg 3994, 493–500, (2006).
  7. G.L. Lilien, P. Kotler. Marketing decision making: A model-building approach. Marketing research 21, 339–341, (1983).
  8. B.L Bowerman, R.T. Connell, and A.B. Koehler. Forecasting, Time Series, and Regression, South-Western College Pub; 4th edition, (2005).
  9. R. Adhikari, & R.K. Agrawal. An Introductory Study on Time Series Modeling and Forecasting. 21–45, (2013).
  10. N.Y. Zainun. Computerized Model to Forecast Low-Cost Housing Demand in Urban Area in Malaysia Using Artificial Neural Networks (ANN). Loughborough University, (2011).
  11. C.D. Lewis. Industrial and Business Forecasting Methods. Butterworths. 2,194–196, (1982).