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Fuzzy Information and Engineering pp 15–23Cite as

Application of Artificial Neural Networks to Classify Water Quality of the Yellow River

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Part of the book series: Advances in Soft Computing ((AINSC,volume 54))

Abstract

Within the period from 2003 to 2005 (high water, normal water and low water) 63 samples are collected and the measurement of 10 chemical variables of the Yellow River of Gansu period, are carried out. These variables are dissolved oxygen (DO), chemical oxygen demand (COD), non-ion ammonia (NH x ), volatilization Hydroxybenzene (OH), cyanide (CN), As, Hg, Cr6 + , Pb, and Cd. For handling the results of all measurements different chemoinformatics methods are employed: (i) The basic statistical methods that uniform design is employed to determinate the data set according to the water quality standard, (ii) MLP neural network (BP) and Probabilistic neural networks (PNN) are used to classify the water quality of different sampling site and different sampling time. The correlation between the water quality classes and chemical measurements is sought. The model between the water quality classes and chemical measurements is built, and these models could quickly, completely and accurately classify the water quality of the Yellow River.

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Author information

Authors and Affiliations

  1. Experiment Center, Northwest University for Nationality, Lanzhou, Gansu, 730030, China

    Li-hua Chen

  2. Chemistry and Chemical Engineering College, LanZhou University, Lanzhou, Gansu, 730030, China

    Xiao-yun Zhang

Authors
  1. Li-hua Chen
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  2. Xiao-yun Zhang
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Editor information

Editors and Affiliations

  1. Guangzhou Higher Education Mega Center, Guangzhou University, 230Wai Huan Xi Road, 510006, China

    Bing-yuan Cao

  2. Department of Mathematics, Hainan Normal University, Haikou, 571158, Hainan, P.R. China

    Cheng-yi Zhang

  3. Department of Electronic Information Engineering, Chongqing University of Science & Technology, 401331, Chongqing

    Tai-fu Li

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© 2009 Springer-Verlag Berlin Heidelberg

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Chen, Lh., Zhang, Xy. (2009). Application of Artificial Neural Networks to Classify Water Quality of the Yellow River. In: Cao, By., Zhang, Cy., Li, Tf. (eds) Fuzzy Information and Engineering. Advances in Soft Computing, vol 54. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88914-4_3

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  • DOI: https://doi.org/10.1007/978-3-540-88914-4_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88913-7

  • Online ISBN: 978-3-540-88914-4

  • eBook Packages: EngineeringEngineering (R0)

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