### Abstract

The attribute reduction is known as the procedure for decreasing the number of features in an information system and its action is a vital phase of data mining processing. In the attribute reduction process, the least subset of attributes is selected (according to rough set theory which is employed as a mathematical tool) from the initial set of attributes with very little loss in information. In this study, a new optimization approach, known as the water cycle algorithm (WCA), has been used for attribute reduction and the rough set theory is employed as a mathematical tool to assess quality of solutions that are produced. The idea of the WC as an optimization algorithm was derived from nature, after examining the whole water cycle process which involves the flow of streams and rivers into the sea in the natural world. The WC-RSAR has been employed in public datasets that are obtainable in UCI. From the findings of the experiments, it has been shown that the suggested method performs equally well or even better than other methods of attribute selection.

Original language | English |
---|---|

Pages (from-to) | 107-117 |

Number of pages | 11 |

Journal | Journal of Theoretical and Applied Information Technology |

Volume | 61 |

Issue number | 1 |

Publication status | Published - 2014 |

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### Keywords

- Attribute reduction
- Rough set theory
- Water cycle algorithm

### ASJC Scopus subject areas

- Computer Science(all)
- Theoretical Computer Science

### Cite this

*Journal of Theoretical and Applied Information Technology*,

*61*(1), 107-117.

**Water cycle algorithm for attribute reduction problems in rough set theory.** / Jabbar, Ahmed; Zainudin, Suhaila.

Research output: Contribution to journal › Article

*Journal of Theoretical and Applied Information Technology*, vol. 61, no. 1, pp. 107-117.

}

TY - JOUR

T1 - Water cycle algorithm for attribute reduction problems in rough set theory

AU - Jabbar, Ahmed

AU - Zainudin, Suhaila

PY - 2014

Y1 - 2014

N2 - The attribute reduction is known as the procedure for decreasing the number of features in an information system and its action is a vital phase of data mining processing. In the attribute reduction process, the least subset of attributes is selected (according to rough set theory which is employed as a mathematical tool) from the initial set of attributes with very little loss in information. In this study, a new optimization approach, known as the water cycle algorithm (WCA), has been used for attribute reduction and the rough set theory is employed as a mathematical tool to assess quality of solutions that are produced. The idea of the WC as an optimization algorithm was derived from nature, after examining the whole water cycle process which involves the flow of streams and rivers into the sea in the natural world. The WC-RSAR has been employed in public datasets that are obtainable in UCI. From the findings of the experiments, it has been shown that the suggested method performs equally well or even better than other methods of attribute selection.

AB - The attribute reduction is known as the procedure for decreasing the number of features in an information system and its action is a vital phase of data mining processing. In the attribute reduction process, the least subset of attributes is selected (according to rough set theory which is employed as a mathematical tool) from the initial set of attributes with very little loss in information. In this study, a new optimization approach, known as the water cycle algorithm (WCA), has been used for attribute reduction and the rough set theory is employed as a mathematical tool to assess quality of solutions that are produced. The idea of the WC as an optimization algorithm was derived from nature, after examining the whole water cycle process which involves the flow of streams and rivers into the sea in the natural world. The WC-RSAR has been employed in public datasets that are obtainable in UCI. From the findings of the experiments, it has been shown that the suggested method performs equally well or even better than other methods of attribute selection.

KW - Attribute reduction

KW - Rough set theory

KW - Water cycle algorithm

UR - http://www.scopus.com/inward/record.url?scp=84896865574&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84896865574&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:84896865574

VL - 61

SP - 107

EP - 117

JO - Journal of Theoretical and Applied Information Technology

JF - Journal of Theoretical and Applied Information Technology

SN - 1992-8645

IS - 1

ER -