Extraction of minimal decision algorithm using rough sets and genetic algorithm

With the performance improvement of computers in recent years, the amount of stored available data is rapidly increasing. But it is also required that the computer fully utilize the stored resources and perform higher-level intelligent jobs. 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. © 2007 Wiley Periodicals, Inc. Syst Comp Jpn, 38(4): 39–51, 2007; Published online in Wiley InterScience (www.interscience. wiley.com). DOI 10.1002/scj.20405