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Author Murakami, M. ♦ Honda, N.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2007
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods
Subject Keyword Intrusion detection ♦ Partitioning algorithms ♦ Humans ♦ Systems engineering and theory ♦ Ink ♦ Engines ♦ Image generation ♦ Training data ♦ Fuzzy logic ♦ Biological neural networks
Abstract The ink drop spread (IDS) method is a modeling technique that is proposed as a new paradigm of soft computing. In this method, the structure of models is determined by the partitioning of the input domain. In order to obtain a high-accuracy model, it is necessary to determine the optimal number of partitions, i.e., structural optimization must be performed. This paper proposes a structural optimization technique for IDS modeling. The IDS model comprises multiple processing units, each of which is a modeling engine that develops a feature of the target system in the form of an easily comprehensible image on a two-dimensional plane. The proposed technique performs structural optimization with a small number of searches by analyzing the image information generated in the processing units instead of evaluating the model error using validation data.
Description Author affiliation: Electro-Commun. Univ., Chofu (Murakami, M.)
ISBN 1424412137
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2007-06-24
Publisher Place USA
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 414.40 kB
Page Count 6
Starting Page 204
Ending Page 209


Source: IEEE Xplore Digital Library