Pre-tender cost estimate of agriculture subsurface drainage projects

Hossam H. Mohmad, Ahmed H. Ibrahim and Heba H. El Nagar

International Journal of Applied Management Science, 2016, vol. 8, issue 4, 271-289

Abstract: Cost estimate at pre-tender stage of subsurface drainage projects could determine whether a project is dropped or continued. Forty one factors that are expected to greatly influence the cost estimate of subsurface drainage at pre-tender stage were identified through a comprehensive literature review. A questionnaire survey was agreed out through 68 qualified subsurface engineers in Egypt, to get the most important cost factors. Through this survey, 12 factors were only considered as the most important cost factors. The neural power program was found appropriate for the development of the suggested model. The desired field information grouped from 61 subsurface drainage projects in Egypt. The best building of the suggested model was identified with RMS = 0.0405 and max absolute error = 4.01%. Testing the validity of the model clearly showed that it has a good prediction capability with a maximum error of 3.51%.

Keywords: pre-tender cost estimation; agriculture; subsurface drainage projects; artificial neural networks; ANNs; regression analysis; sensitivity analysis; Egypt. (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:ids:injams:v:8:y:2016:i:4:p:271-289

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