201. Learning: An Effective Approach in Endgame Chess Board Evaluation
- Author
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S. kouno, Michiyuki Hirokane, and Y. Nomura
- Subjects
Knowledge representation and reasoning ,business.industry ,Computer science ,Computation ,computer.software_genre ,Machine learning ,Knowledge acquisition ,Cross-validation ,Genetic algorithm ,Artificial intelligence ,Data mining ,Rough set ,business ,Decision table ,Representation (mathematics) ,computer ,Algorithm - Abstract
In civil engineering, it is crucial to reuse knowledge which has been accumulated through the experience of engineers, etc. For this purpose, it is necessary to establish a method for knowledge acquisition and a method for explicit representation of the acquired knowledge. This paper applies the genetic algorithm to the process of deriving a decision algorithm from instances by using rough sets, and proposes a method of deriving a simple and useful decision algorithm with a relatively small amount of computation. A decision algorithm is actually derived from the data on accident instances at actual construction sites, and the recognition rate and other performance measures are investigated by the k-fold cross validation method.
- Published
- 2007