Assessment of Water Quality Using Multi-Layered Mamdani Fuzzy Inference Expert System

Author:

Ahmad Gulzar1ORCID,Aqeel Sehrish2,Zafar Zobia3,Fatima Kanza3

Affiliation:

1. Minhaj University, Lahore, Pakistan

2. University of Malaysia, Sarawak, Malaysia

3. University of South Asia, Pakistan

Abstract

In this chapter, a new multi-layered mamdani fuzzy inference system (ML-MFIS) is proposed for the assessment of water quality (AWQ). The proposed AWQ-ML-MFIS expert system can categorize the level of water quality into excellent, normal, or dangerous for health (polluted). AWQ-ML-MFIS expert system for drinking water is developed by the guidelines from the World Health Organization (WHO) and Pakistan's Punjab environmental quality standard. AWQ-ML-MFIS expert system uses input water parameters such as bacterial, physical, chemical, and radioactive for different layers. The chemical parameters are further divided into essential inorganics, toxic inorganics, and organics. This chapter also analyses the intensities of the parameters and the results achieved by using the proposed AWQ-ML-MFIS expert system. All these parameters and results are discussed with the experts of the Pakistan Council of Scientific and Industrial Research (PCSIR), Lahore. The accuracy of the proposed AWQ-ML-MFIS Expert System is more accurate as compared to others approaches used for it.

Publisher

IGI Global

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