ARCOM

Abstracts – Browse Results

Click on the titles below to expand the information about each abstract.
Viewing 8 results ...

Christodoulou, S E, Ellinas, G N and Aslani, P (2009) Disorder considerations in resource-constrained scheduling. Construction Management and Economics, 27(03), 229–40.

Hui, E C-M and Fung, H H-K (2009) Real estate development as real options. Construction Management and Economics, 27(03), 221–7.

Jia, Y A, Rowlinson, S, Kvan, T, Lingard, H C and Yip, B (2009) Burnout among Hong Kong Chinese architecture students: the paradoxical effect of Confucian conformity values. Construction Management and Economics, 27(03), 287–98.

Leiringer, R, Green, S D and Raja, J Z (2009) Living up to the value agenda: the empirical realities of through-life value creation in construction. Construction Management and Economics, 27(03), 271–85.

Ping Ho, S, Lin, Y-H, Wu, H-L and Chu, W (2009) Empirical test of a model for organizational governance structure choices in construction joint ventures. Construction Management and Economics, 27(03), 315–24.

Pulket, T and Arditi, D (2009) Construction litigation prediction system using ant colony optimization. Construction Management and Economics, 27(03), 241–51.

Type: Journal Article
Keywords: ant colony algorithm; artificial intelligence; case-based reasoning; decision trees; litigation; neural networks
ISBN/ISSN: 0144-6193
URL: https://doi.org/10.1080/01446190802714781
Abstract:
The frequency of construction litigation has increased over the years, making litigation a costly and time-consuming activity. It is in the interests of all parties to a construction contract to avoid litigation. A tool (Ant Miner) is proposed to predict the outcome of construction litigation, hence encouraging the parties to settle out of court. Ant Miner, a rule-based classification system extracts classification rules by using ant colony optimization. It is used on 151 Illinois circuit court cases filed in the period 1987-2005. The prediction model is composed of data consolidation, attribute selection, classification and assessment. The results provide evidence that Ant Miner performs better than models used in earlier studies and that the rule sets discovered by this tool are highly interpretable, but that this tool suffers a great deal from noisy data. If the parties involved in a dispute have access to the proposed system that predicts the decision of the courts with higher accuracy and reliability than before, then they are expected to avoid litigation and settle out of court in order to save considerable time, money and aggravation.