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Dergiler / Marine Science and Technology Bulletin / 2012 / Volume: 1 Issue: 1

Various inference systems for classification of water quality status: A case study

Olcay Hisar(Canakkale Onsekiz Mart University, Marine Science and Technology Faculty, Canakkale, Turkey)
Adem Yavuz Sönmez(Kastamonu University, Fisheries Faculty, Kastamonu, Turkey)
Hasan Kaya(Canakkale Onsekiz Mart University, Marine Science and Technology Faculty, Canakkale, Turkey)
Şükriye Aras Hisar(Canakkale Onsekiz Mart University, Marine Science and Technology Faculty, Canakkale, Turkey)
Sayfa
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Yayın Tarihi
2012-12-20
DOI
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Yapay Zeka Hızlı Bakış & Çıkarımlar

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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

In conclusion, it can be proposed that fuzzy logic assessment methods may also be used as an alternative tool for decision-making in environmental management.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Water quality is considered one of the main factors controlling health and the disease state of humans and animals.
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Temel Bulgular & Veri:Four assessment methods (two pollution indexes and two fuzzy mathematical models) were used to understand the water quality parameter levels and characteristic accurately.
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Sonuç & Katkı:In conclusion, it can be proposed that fuzzy logic assessment methods may also be used as an alternative tool for decision-making in environmental management.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Water quality · Fuzzy logic · Physico-chemical parameters

Abstract

Water quality is considered one of the main factors controlling health and the disease state of humans and animals. Four assessment methods (two pollution indexes and two fuzzy mathematical models) were used to understand the water quality parameter levels and characteristic accurately. Several physico-chemical parameters such as dissolved oxygen, nitrate, nitrite, phosphate, chlor, sulphure and total organic carbon were measured in Karasu River, Turkey. Water quality was assessed as class IV (heavy polluted) in A, B, C and D stations and class III (polluted) in station E with single-factor index method. It was also identified as class III (polluted) for waters in A, B, C and D stations and class II (slightly polluted) for water in station E with the comprehensive index model. Using the two fuzzy mathematical methods (single-factor deciding and weighted average models), the water quality was determined as II, II, III, III and II classes for waters in A, B, C, D and E stations, respectively. In conclusion, it can be proposed that fuzzy logic assessment methods may also be used as an alternative tool for decision-making in environmental management.

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Bu Makaleye Atıf Yap

Hisar, O., Sönmez, A. Y., Kaya, H., Hisar, Ş. A. (2012). Various inference systems for classification of water quality status: A case study. Marine Science and Technology Bulletin, Volume: 1 Issue: 1. https://ajindex.com/articles/1286329

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Kaynakça (17)

  1. Alam, M. G. M., Tanaka, A., Stagnitti, F., Allinson, G., and T. Maekawa. 2001. Observations on the Effects of Caged Carp Culture on Water and Sediment Metal Concentrations in Lake Kasumigaura, Japan. Ecotoxicology and Environmental Safety, 48: 107-115.
  2. APHA (American Public Health Association), 1998. Standard Methods for the Examination of Water and Wastewater, 20th ed., AWWAWPCF, Washington, DC.
  3. Chen, T. B., Zheng, Y. M., Lei, M., Huang, Z. C., Wu, H. T., Chen, H., Fan, K. K., Yu, K., Wu, X., and Q. Z. Tian. 2005. Assessment of Heavy Metal Pollution in Surface Soils of Urban Parks in Beijing, China. Chemosphere, 60(4): 542–551.
  4. Duque, W. O., Huguet, N. F., Domindo, J. L., and M. Schuhmacher. 2006. Assessing Water Quality in Rivers With Fuzzy Inference Systems: A Case Study. Environmental International, 32: 733742.
  5. Geldermann, J., Spengler, T., and O. Rentz. 2000. Fuzzy Outranking for Environmental Assessment. Case Study: Iron and Steel Making Industry. Fuzzy Sets and Systems, 115: 45–65. Icaga, Y. 2007. Fuzzy Evaluation of Water Quality Classification. Ecological Indicators, 7:710–718.
  6. Jain, C. K., Gupta, H., and G. J. Chakrapani. 2008. Enrichment and Fractionation of Heavy Metals in Bed Sediments of River Narmada, India. Environmental Monitoring and Assessment, 141:35–47.
  7. Lermontov, A., Ykoyama, L., Lermontov, M., Augusta, M., and S. Machado. 2009. River Quality Analysis Using Fuzzy Water Quality Index: Riberia do Iguape River Watershed, Brazil. Ecological Indicators, 9: 1188-1197.
  8. Liou, S. M., Lo, S. L., and C. Y. Hu. 2003. Application of Two-Stage Fuzzy Set Theory to River Quality Evaluation in Taiwan Source. Water Research, 37 (6): 1406–1416.
  9. Liou, Y. T., and S. L. Lo. 2005. A Fuzzy Index Model for Trophic Status Evaluation of Reservoir Waters. Water Research, 39: 1415–1423.
  10. Ludwig, B., and I. Tulbure. 1996. Contributions to an Aggregated Environmental Pollution Index. In: Proceedings of the Intersociety Energy Conversion Engineering Conference, 3:2144–2149.
  11. Rahana, S., and P. P. Mujumdar. 2009. An Imprecise Fuzzy Risk Approach for Water Quality Management of a River System. Journal of Environmental Management, 90: 3653–3664.
  12. Sadiq, R., and T. Husain. 2005. Fuzzy-based Methodology for an Aggregative Environmental Risk Assessment: A Case Study of Drilling Waste. Environmental Modelling & Software, 20 (1): 33Shen, G., Lu, Y., Wang, M., and Y. Sun. 2005. Status and Fuzzy Comprehensive Assessment of Combined Heavy Metal and Organo-chlorine Pesticide Pollution in the Taihu Lake Region of China. Journal of Environmental Management, 76: 355–362.
  13. Silvert, W. 2000. Fuzzy Indices of Environmental Conditions. Ecological Modelling, 130: 111–119.
  14. Sönmez, A. Y. 2011. Determination of Heavy Metal Pollution in Karasu River and Its Evaluation by Fuzzy Logic. PhD Thesis. Atatürk University Graduate School of Agriculture Faculty Departmant of Fishery Sciences.
  15. Wang, L. J., and Z. H. Zou. 2008. Application of Improved Attributes Recognition Method in Water Quality Assessment. Chinese Journal of Environmental Engineering, 2 (4): 553–556.
  16. Wei-Xin, L. I., Xu-Xiang, Z., Bing, W. U., Shi-Lei, S., Yan-Song, C., Wen-Yang, P., Da-Yong, Z., and C. Shu-Pei. 2008. A Comparative Analysis of Environmental Quality Assessment Methods for Heavy Metal Contaminated Soils. Pedosphere, 18 (3):344-352.
  17. WPCR, 2004. Water Pollution and Control Regulations. Offical Gazette 31.12.2004, No:25687.