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A Rough Set Based Model in Water Quality Analysis

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  • Ping-Feng Pai
  • Fong-Chuan Lee

Abstract

Due to pollution caused by the expansion of human activities and economic development, water quality has gradually deteriorated in many areas of the world. Therefore, analysis of water quality becomes one of the most essential issues of modern civilization. Integrated interdisciplinary modeling techniques, providing reliable, efficient, and accurate representation of the complex phenomenon of water quality, have gained attention in recent years. With the ability to deal with both numeric and nominal information, and express knowledge in a rule-based form, the Rough Set Theory (RST) has been successfully employed in many fields. However, the application of RST has not been widely investigated in water quality analysis. The reducts generated by RST models become very time-consuming as the size of the problem increases. Using multinomial logistics regression (MLR) techniques to provide reducts of RST models, this investigation develops a hybrid Multinomial Logistic Regression and Rough Set Theory (MLRRST) model to analyze relations between degrees of water pollution and environmental factors in Taiwan. Empirical results indicate that the MLRRST model could analyze water qualities efficiently and accurately, and yield decision rules for the staff of water quality management. Thus, the proposed model is a promising and helpful scheme in analyzing water quality. Copyright Springer Science+Business Media B.V. 2010

Suggested Citation

  • Ping-Feng Pai & Fong-Chuan Lee, 2010. "A Rough Set Based Model in Water Quality Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(11), pages 2405-2418, September.
    • Handle: RePEc:spr:waterr:v:24:y:2010:i:11:p:2405-2418
    DOI: 10.1007/s11269-009-9558-3
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    1. Maria Diamantopoulou & Vassilis Antonopoulos & Dimitris Papamichail, 2007. "Cascade Correlation Artificial Neural Networks for Estimating Missing Monthly Values of Water Quality Parameters in Rivers," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(3), pages 649-662, March.
    2. Dimitras, A. I. & Slowinski, R. & Susmaga, R. & Zopounidis, C., 1999. "Business failure prediction using rough sets," European Journal of Operational Research, Elsevier, vol. 114(2), pages 263-280, April.
    3. X. Qin & G. Huang, 2009. "An Inexact Chance-constrained Quadratic Programming Model for Stream Water Quality Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(4), pages 661-695, March.
    4. Ajit Singh & S. Ghosh & Pankaj Sharma, 2007. "Water quality management of a stretch of river Yamuna: An interactive fuzzy multi-objective approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(2), pages 515-532, February.
    5. Sanchis, A. & Segovia, M.J. & Gil, J.A. & Heras, A. & Vilar, J.L., 2007. "Rough Sets and the role of the monetary policy in financial stability (macroeconomic problem) and the prediction of insolvency in insurance sector (microeconomic problem)," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1554-1573, September.
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    Cited by:

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    2. Huyong Yan & Guoyin Wang & Di Wu & Yu Huang & Mingsheng Shang & Jianjun Xu & Kun Shan & Xiaoyu Shi & Jianhua Dong & Lei Feng & Botian Zhou & Ye Yuan & Yufei Zhao, 2017. "Water Bloom Precursor Analysis Based on Two Direction S-Rough Set," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(5), pages 1435-1456, March.
    3. Ping-Feng Pai & Lan-Lin Li & Wei-Zhan Hung & Kuo-Ping Lin, 2014. "Using ADABOOST and Rough Set Theory for Predicting Debris Flow Disaster," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(4), pages 1143-1155, March.
    4. Gao, Yang & Zhang, Xiao & Wu, Lei & Yin, Shijiu & Lu, Jiao, 2017. "Resource basis, ecosystem and growth of grain family farm in China: Based on rough set theory and hierarchical linear model," Agricultural Systems, Elsevier, vol. 154(C), pages 157-167.
    5. Maryam Zavareh & Viviana Maggioni, 2018. "Application of Rough Set Theory to Water Quality Analysis: A Case Study," Data, MDPI, vol. 3(4), pages 1-15, November.

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