الفهرس | Only 14 pages are availabe for public view |
Abstract Developing a new technique for pre-tender cost estimate of agriculture subsurface drainage projects is the aim of this study. Through developing a model that is able to predict cost of subsurface projects at early stages of project design before preparing the detailed bill of quantity as an alternative technique instead of traditional one, which will be a helpful tool for drainage consulting firm in Egypt. Also it is considered as judgment tool to determine priority of implementing projects according to available general budget for projects which have the same conditions. Several techniques were adopted carefully to identify the factors that affect cost of subsurface drainage projects at pre-tender stage through reviewing literature studies, bill of quantities and expert’s interviews. Forty one factors were collected and grouped in six groups. A questionnaire survey was agreed out through sixty eight qualified subsurface engineers and contractors in Egypt to get the most important factors. Based on the result of this survey, twelve factors that have the greatest effect were identified. These factors are: National rules and regulations, feedback information from previous projects, leveling project area on new updated maps and accuracy of maps information, type of donor finance, inflation rate, area of land to be drainaged, quantity of laterals used, quantity of plastic collector drains used, quantity of reinforced concrete collector drains, quantity of pitching with stones and mortar, number of precast reinforced concrete manholes, and another requirement cost for construction site. These most important factors were used for developing models by using regression analysis and artificial neural network. Application SPSS version 19.0.0 and Neural Power Professional Version 2.50 were used for developing the desired models. These models used the twelve input parameters to predict cost of subsurface drainage (output). The required information collected from 61 real |