Knowledge acquisition methods for expert systems based on machine learning

被引:0
作者
Ma, Xin [1 ]
Liu, Changlong [1 ]
Zhang, Beike [1 ]
机构
[1] College of Information Science and Technology, Beijing University of Chemical and Technology, Beijing 100029, China
来源
Beijing Huagong Daxue Xuebao (Ziran Kexueban)/Journal of Beijing University of Chemical Technology (Natural Science Edition) | 2008年 / 35卷 / 05期
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摘要
The objective of this paper is to present a hybrid method for knowledge acquisition which combines rule acquisition methods based on historical data with model-based methods. The former method derives rules through rough set reduction of a genetic algorithm, while the latter transforms the cause-effect graph to rules by using the automatic reasoning result of a signed directed graph (SDG). Using the rules obtained by the above hybrid method to enrich the rules base provides knowledge covering the whole flow process. An example of the use of the method is given for an electric desalting system.
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页码:89 / 93
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