Extraction Method Based on Rough Set Theory of Rule-Type Knowledge from Diagnostic Cases of Slope-Failure Danger Levels

Furuta, Hiroyuki; Hirokane, Michiyuki; Mikumo, Yukihiro

doi:10.1007/978-3-7908-1883-3_10

Cited by 5 publications

(3 citation statements)

References 4 publications

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“…For more applications of the rough set theory in diagnosis monitoring, the reader is referred to Furuta et al (1998), Greco et al (1998c), Keiser et al (1992), Lambert‐Torres et al (1999), Lingras (1996), Nowicki et al (1992b), Stefanowski et al (1992), Swiniarski et al (1995) and Yang et al (2001).…”

Section: Applications Of the Rough Set Theorymentioning

confidence: 99%

The rough set theory and applications

Wu¹,

Yue

Li³

et al. 2004

Engineering Computations

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This paper presents a comprehensive review of the available literature on applications of the rough set theory. Concepts of the rough set theory are discussed for approximation, dependence and reduction of attributes, decision tables and decision rules. The applications of rough sets are discussed in pattern recognition, information processing, business and finance, industry, environment engineering, medical diagnosis and medical data analysis, system fault diagnosis and monitoring and intelligent control systems. Development trends and future efforts are outlined. An extensive list of references is also provided to encourage interested readers to pursue further investigations.

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Section: Applications Of the Rough Set Theorymentioning

confidence: 99%

The rough set theory and applications

Wu¹,

Yue

Li³

et al. 2004

Engineering Computations

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“…Using rough set theory, AttohOkine proposed decision support systems for pavement rehabilitation and maintenance [7], Kaname et al presented a rough set approach to information retrieval [8], and Furuta et al extracted experiential knowledge of experts from diagnostic results of the danger levels of slope-failure as decision tables of a minimal decision algorithm [9]. These studies showed that rough set theory could be a useful tool for information analysis of data having the characteristics of imprecision, incompleteness and unobtainable.…”

Section: Introductionmentioning

confidence: 99%

Rough set algorithm for crack category determination of reinforced concrete structures

Kim¹,

Kim

Lee

2009

Advances in Engineering Software

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“…The authors applied the rough sets method [7] proposed by Pawlak, which is attracting attention as a knowledge acquisition technique, and proposed a method of extracting empirical knowledge inherent in the results of diagnosis by experts [8][9][10]. A problem of knowledge acquisition by the rough sets method is that a large number of rules are extracted.…”

Section: Introductionmentioning

confidence: 99%

Extraction of minimal decision algorithm using rough sets and genetic algorithm

HirokaneMichiyuki¹,

KonishiHideyuki²,

MiyamotoAyaho³

et al. 2007

Systems & Computers in Japan

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SUMMARYWith 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.

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Extraction Method Based on Rough Set Theory of Rule-Type Knowledge from Diagnostic Cases of Slope-Failure Danger Levels

Cited by 5 publications

References 4 publications

The rough set theory and applications

The rough set theory and applications

Rough set algorithm for crack category determination of reinforced concrete structures

Extraction of minimal decision algorithm using rough sets and genetic algorithm

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