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Baker, S, Ponniah, D and Smith, S (1999) Risk response techniques employed currently for major projects. Construction Management and Economics, 17(02), 205-13.
Baldwin, A N, Austin, S A, Hassan, T M and Thorpe, A (1999) Modelling information flow during the conceptual and schematic stages of building design. Construction Management and Economics, 17(02), 155-67.
Chan, A P C (1999) Modelling building durations in Hong Kong. Construction Management and Economics, 17(02), 189-96.
Goh, B-H (1999) An evaluation of the accuracy of the multiple regression approach in forecasting sectoral construction demand in Singapore. Construction Management and Economics, 17(02), 231-41.
Green, S D (1999) The missing arguments of lean construction. Construction Management and Economics, 17(02), 133--7.
Gyi, D E, Gibb, A G F and Haslam, R A (1999) The quality of accident and health data in the construction industry: interviews with senior managers. Construction Management and Economics, 17(02), 197-204.
Li, H and Love, P E D (1999) Combining rule-based expert systems and artificial neural networks for mark-up estimation. Construction Management and Economics, 17(02), 169-76.
- Type: Journal Article
- Keywords: explanation facility; hyCMEd system; mark-up decision; rule extraction
- ISBN/ISSN: 0144-6193
- URL: https://doi.org/10.1080/014461999371664
- Abstract:
Rule-based expert systems and artificial neural networks are two major systems for developing intelligent decision support systems. The integration of the two systems can generate a new system which shares the strengths of both rule-based and artificial neural network systems. This research presents a computer based mark-up decision support system called InMES (integrated mark-up estimation system) that integrates a rule-based expert system and an artificial neural network (ANN) based expert system. The computer system represents an innovative approach for estimating a contractor’ s mark-up percentage for a construction project. A rule extraction method is developed to generate rules from a trained ANN. By using the explanation facility embedded in the rule-based expert system, InMES provides users with a clear explanation to justify the rationality of the estimated mark-up output. Cost data derived from a contractor’ s successful bids were used to train an ANN and, in conjunction with a rule-based expert system, select the expected mark-up for a project. The combination of both ANN- and rule-based expert systems for estimating mark-up allows significant benefits to be made from each individual system, such as understanding why and how the estimated mark-up was derived and also the effects of imposing rules and constraints on a company’s mark-up estimation. The mark-up decision support system presented can assist contractors in preparing a rational mark-up percentage for a project. Moreover, InMES as proposed will assist contractors in their tender decision making, that is, whether or not to submit a bid for a project considering the estimated mark-up.
Loosemore, M (1999) Bargaining tactics in construction disputes. Construction Management and Economics, 17(02), 177-88.
Proverbs, D G, Holt, G D and Olomolaiye, P O (1999) European construction contractors: a productivity appraisal of in situ concrete operations. Construction Management and Economics, 17(02), 221-30.
Ray, R S, Hornibrook, J, Skitmore, M R and Zarkada-Fraser, A (1999) Ethics in tendering: a survey of Australian opinion and practice. Construction Management and Economics, 17(02), 139-53.
Sozen, Z and Kucuk, M A (1999) Secondary subcontracting in the Turkish construction industry. Construction Management and Economics, 17(02), 215-20.
Tan, W (1999) Construction cost and building height. Construction Management and Economics, 17(02), 129-32.