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Development of Fuzzy Knowledge-Based System for Water Quality Assessment in River Ganga

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Soft Computing for Problem Solving 2019

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1139))

Abstract

Rivers are playing an important role in human life and wildlife but due to pollution the quality of river water is extremely deteriorated. The assessment of water quality is a very indeterminate task and associates a lot of uncertainty and subjectivity in the decision making. To cope with this situation, computational intelligence techniques are found competent to develop models for water quality assessment. One of the computational intelligence techniques, fuzzy logic is used to implement such models. In this manuscript, a fuzzy knowledge-based system is developed to classify the water quality of river Ganga in three groups. The open-access software ‘Guaje’ is used to implement the proposed model. The analysis of the results is presented in terms of interpretability and accuracy which are found satisfactory.

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Author information

Authors and Affiliations

  1. Department of Information Technology, Babu Banarsi Das Northern India Institute of Technology, Lucknow, India

    Praveen Kumar Shukla

Authors
  1. Praveen Kumar Shukla
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Correspondence to Praveen Kumar Shukla .

Editor information

Editors and Affiliations

  1. School of Mathematics, Computer Science and Engineering, Liverpool Hope University, Liverpool, UK

    Atulya K. Nagar

  2. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, India

    Kusum Deep

  3. Department of Mathematics, South Asian University, New Delhi, Delhi, India

    Jagdish Chand Bansal

  4. Department of Mathematics, National Institute of Technology Silchar, Silchar, India

    Kedar Nath Das

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Shukla, P.K. (2020). Development of Fuzzy Knowledge-Based System for Water Quality Assessment in River Ganga. In: Nagar, A., Deep, K., Bansal, J., Das, K. (eds) Soft Computing for Problem Solving 2019 . Advances in Intelligent Systems and Computing, vol 1139. Springer, Singapore. https://doi.org/10.1007/978-981-15-3287-0_2

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