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Construction litigation prediction system using ant colony optimization

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Author Info
Thaveeporn Pulket
David Arditi
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.

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File URL: http://www.informaworld.com/openurl?genre=article&doi=10.1080/01446190802714781&magic=repec&7C&7C8674ECAB8BB840C6AD35DC6213A474B5
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Publisher Info
Article provided by Taylor and Francis Journals in its journal Construction Management and Economics.

Volume (Year): 27 (2009)
Issue (Month): 3 ()
Pages: 241-251
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Handle: RePEc:taf:conmgt:v:27:y:2009:i:3:p:241-251

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Related research
Keywords: Ant colony algorithm; artificial intelligence; case-based reasoning; decision trees; litigation; neural networks;

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This page was last updated on 2009-12-5.


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