Improving classification accuracy of project dispute resolution using hybrid artificial intelligence and support vector machine models
Author:
Publisher
Elsevier BV
Subject
Artificial Intelligence,Computer Science Applications,General Engineering
Reference28 articles.
1. Predicting the outcome of construction litigation using neural networks;Arditi;Computer-Aided Civil and Infrastructure Engineering,1998
2. Predicting the outcome of construction litigation using boosted decision trees;Arditi;Journal of Computing in Civil Engineering,2005
3. Predicting the outcome of construction litigation using an integrated artificial intelligence model;Arditi;Journal of Computing in Civil Engineering,2010
4. Comparison of case-based reasoning and artificial neural networks;Arditi;Journal of Computing in Civil Engineering,1999
5. Using case-based reasoning to predict the outcome of construction litigation;Arditi;Computer-Aided Civil and Infrastructure Engineering,1999
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