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논문 기본 정보

자료유형
학술저널
저자정보
El-Sawalhi, Nabil Ibrahim (Depty Dean faculty of Engineering, The Islamic University-Gaza) Shehatto, Omar (The Islamic University-Gaza)
저널정보
한국건설관리학회 Journal of construction engineering and project management Journal of construction engineering and project management 제4권 제4호
발행연도
2014.1
수록면
9 - 16 (8page)

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The purpose of this paper is to develop a model for forecasting early design construction cost of building projects using Artificial Neural Network (ANN). Eighty questionnaires distributed among construction organizations were utilized to identify significant parameters for the building project costs. 169 case studies of building projects were collected from the construction industry in Gaza Strip. The case studies were used to develop ANN model. Eleven significant parameters were considered as independent input variables affected on "project cost". The neural network model reasonably succeeded in estimating building projects cost without the need for more detailed drawings. The average percentage error of tested dataset for the adapted model was largely acceptable (less than 6%). Sensitivity analysis showed that the area of typical floor and number of floors are the most influential parameters in building cost.

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