A novel self-optimizing approach for knowledge acquisition

作者：Pan D^*; Zheng QL; Zeng A; Hu JS

来源：IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans , 2002, 32(4): 505-514.

DOI：10.1109/TSMCA.2002.804809

• difference comparison table (DCT)
• knowledge acquisition
• optimization methodology

The attribute reduction and the rule generation (the attribute value reduction) are two main processes for knowledge acquisition. A self-optimizing approach based on a difference comparison table (DCT) for knowledge acquisition aimed at the above processes was proposed. In the attribute reduction process, the conventional logic computation was transferred to a matrix computation along with some added thoughts on the evolution computation used to construct the self-adaptive optimizing algorithm (SAOA). In addition, some subalgorithms and proofs were presented in detail. In the rule generation process, the orderly attribute value reduction algorithm (OAVRA), which simplified the complexity of rule knowledge, was presented. The approach provided an effective and efficient method for knowledge acquisition that was supported by the experimentation.

• 出版日期2002-7
• 单位华南理工大学