IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v24y2010i11p2405-2418.html
   My bibliography  Save this article

A Rough Set Based Model in Water Quality Analysis

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11269-009-9558-3
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11269-009-9558-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. 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.
    3. 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.
    4. 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.
    5. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. Yuyu Liu & Caizhi Sun & Shiguo Xu, 2013. "Eco-Efficiency Assessment of Water Systems in China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(14), pages 4927-4939, November.
    4. 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.
    5. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Huapeng Qin & Jingjing Jiang & Guangtao Fu & Ying Zheng, 2013. "Optimal Water Quality Management Considering Spatial and Temporal Variations in a Tidal River," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(3), pages 843-858, February.
    3. Zhou, Fanyin & Fu, Lijun & Li, Zhiyong & Xu, Jiawei, 2022. "The recurrence of financial distress: A survival analysis," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1100-1115.
    4. Beynon, Malcolm J. & Peel, Michael J., 2001. "Variable precision rough set theory and data discretisation: an application to corporate failure prediction," Omega, Elsevier, vol. 29(6), pages 561-576, December.
    5. Shrutika Mishra & A. R. Tripathi, 2021. "AI business model: an integrative business approach," Journal of Innovation and Entrepreneurship, Springer, vol. 10(1), pages 1-21, December.
    6. Zopounidis, Constantin & Doumpos, Michael, 2001. "A preference disaggregation decision support system for financial classification problems," European Journal of Operational Research, Elsevier, vol. 130(2), pages 402-413, April.
    7. Haoming Wang & Xiangdong Liu, 2021. "Undersampling bankruptcy prediction: Taiwan bankruptcy data," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-17, July.
    8. H. Ooghe & S. De Prijcker, 2006. "Failure process and causes of company bankruptcy: a typology," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 06/388, Ghent University, Faculty of Economics and Business Administration.
    9. Beynon, Malcolm J., 2005. "A novel technique of object ranking and classification under ignorance: An application to the corporate failure risk problem," European Journal of Operational Research, Elsevier, vol. 167(2), pages 493-517, December.
    10. M. Islam & Rehan Sadiq & Manuel Rodriguez & Homayoun Najjaran & Alex Francisque & Mina Hoorfar, 2013. "Evaluating Water Quality Failure Potential in Water Distribution Systems: A Fuzzy-TOPSIS-OWA-based Methodology," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 2195-2216, May.
    11. Paramonovs Sergejs & Ijevleva Ksenija, 2015. "The Role of Marketing Tools in the Improvement of Consumers Financial Literacy," Acta Universitatis Sapientiae, Economics and Business, Sciendo, vol. 27(1), pages 40-45, December.
    12. du Jardin, Philippe & Séverin, Eric, 2011. "Predicting corporate bankruptcy using a self-organizing map: An empirical study to improve the forecasting horizon of a financial failure model," MPRA Paper 44262, University Library of Munich, Germany.
    13. Bojan Srdjevic & Yvonilde Medeiros, 2008. "Fuzzy AHP Assessment of Water Management Plans," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(7), pages 877-894, July.
    14. Kartashova Olga Ivanovna & Molchanova Olga Vladimirovna & Axana Turgaeva, 2018. "Insurance Risks Management Methodology," JRFM, MDPI, vol. 11(4), pages 1-15, October.
    15. Salvatore Barbagallo & Simona Consoli & Nello Pappalardo & Salvatore Greco & Santo Zimbone, 2006. "Discovering Reservoir Operating Rules by a Rough Set Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(1), pages 19-36, February.
    16. Wolfgang K. Härdle & Rouslan A. Moro & Dorothea Schäfer, 2004. "Rating Companies with Support Vector Machines," Discussion Papers of DIW Berlin 416, DIW Berlin, German Institute for Economic Research.
    17. Taheri, Mozhdeh & van Geenhuizen, Marina, 2016. "Teams' boundary-spanning capacity at university: Performance of technology projects in commercialization," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 31-43.
    18. Zopounidis, Constantin & Doumpos, Michael, 2002. "Multicriteria classification and sorting methods: A literature review," European Journal of Operational Research, Elsevier, vol. 138(2), pages 229-246, April.
    19. Fayçal Mraihi, 2016. "Distressed Company Prediction Using Logistic Regression: Tunisian’s Case," Quarterly Journal of Business Studies, Research Academy of Social Sciences, vol. 2(1), pages 34-54.
    20. Zopounidis, C., 1999. "Multicriteria decision aid in financial management," European Journal of Operational Research, Elsevier, vol. 119(2), pages 404-415, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:24:y:2010:i:11:p:2405-2418. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.