A study on the modeling ability of the IDS method: A soft computing technique using pattern-based information processing

被引：0
|
作者：
Murakami, Masayuki [1 ]
Honda, Nakaji [1 ]
机构：
[1] Department of Systems Engineering, The University of Electro-Communications, Chofu, Tokyo, 182-8585, Japan
来源：
International Journal of Approximate Reasoning | 2007年 / 45卷 / 03期
关键词：
The ink drop spread (IDS) method is a modeling technique developed by algorithmically mimicking the information-handling processes of the human brain. This method has been proposed as a new approach to soft computing. IDS modeling is characterized by processing that uses intuitive pattern information instead of complex formulas; and it is capable of stable and fast convergences. This paper investigates the modeling ability of the IDS method based on three typical benchmarks. Experimental results demonstrated that the IDS method can handle various modeling targets; ranging from logic operations to complex nonlinear systems; and that its modeling performance is satisfactory in comparison with that of feedforward neural networks. © 2006 Elsevier Inc. All rights reserved;
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页码：470 / 487
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