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AbouRizk, S and Shi, J (1994) Automated Construction‐Simulation Optimization. Journal of Construction Engineering and Management, 120(02), 374–85.

AbouRizk, S M, Halpin, D W and Wilson, J R (1994) Fitting Beta Distributions Based on Sample Data. Journal of Construction Engineering and Management, 120(02), 288–305.

Bai, Y and Amirkhanian, S N (1994) Knowledge‐Based Expert System for Concrete Mix Design. Journal of Construction Engineering and Management, 120(02), 357–73.

Everett, J G and Slocum, A H (1994) Automation and Robotics Opportunities: Construction versus Manufacturing. Journal of Construction Engineering and Management, 120(02), 443–52.

Farid, F and Koning, T L (1994) Simulation Verifies Queuing Program for Selecting Loader‐Truck Fleets. Journal of Construction Engineering and Management, 120(02), 386–404.

Furuya, N, Yamaoka, R and Paulson, B C (1994) Construction of Akashi‐Kaikyo Bridge West Anchorage. Journal of Construction Engineering and Management, 120(02), 337–56.

Hinze, J and Tracey, A (1994) The Contractor‐Subcontractor Relationship: The Subcontractor's View. Journal of Construction Engineering and Management, 120(02), 274–87.

Ndekugri, I and Turner, A (1994) Building Procurement by Design and Build Approach. Journal of Construction Engineering and Management, 120(02), 243–56.

Nishigaki, S, Vavrin, J, Kano, N, Haga, T, Kunz, J C and Law, K (1994) Humanware, Human Error, and Hiyari‐Hat: A Template of Unsafe Symptoms. Journal of Construction Engineering and Management, 120(02), 421–42.

Pin, T H and Scott, W F (1994) Bidding Model for Refurbishment Work. Journal of Construction Engineering and Management, 120(02), 257–73.

Severson, G D, Russell, J S and Jaselskis, E J (1994) Predicting Contract Surety Bond Claims Using Contractor Financial Data. Journal of Construction Engineering and Management, 120(02), 405–20.

Thomas, H R, Smith, G R and Mellott, R E (1994) Interpretation of Construction Contracts. Journal of Construction Engineering and Management, 120(02), 321–36.

Williams, T P (1994) Predicting Changes in Construction Cost Indexes Using Neural Networks. Journal of Construction Engineering and Management, 120(02), 306–20.

  • Type: Journal Article
  • Keywords: Neural networks; Construction costs; Estimation; Computer applications; Cost analysis;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(1994)120:2(306)
  • Abstract:
    Construction cost indexes provide a comparison of cost changes from period to period for a fixed quantity of goods or services. Back‐propagation neural‐network models have been developed to predict the change in the ENR construction cost index for one month and six months ahead. A training set of macroeconomic data was developed for the period from 1967 to 1991. The neural‐network models use inputs including recent trends in the index, the prime lending rate, housing starts, and the month of the year. Output from the neural‐network models was compared with predictions made by exponential smoothing and simple linear regression. The prediction produced by the neural network gave a greater error than either exponential smoothing or linear regression. It can be concluded that the movement of the cost indexes is a complex problem that cannot be predicted accurately by a back‐propagation neural‐network model.