Water Quality Analysis using Adaptive Network-Based Fuzzy Inference System |
Author(s): |
| Jignesh Jambukiya , L.D. College of Engineering; M. B. Dholakia, L.D. College of Engineering |
Keywords: |
| Adaptive Neuro Fuzzy Inference System; Water Quality Parameter; Dissolved Oxygen; Biochemical Oxygen Demand |
Abstract |
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Evaluation of Water characteristics in general and water quality in particular are necessary to enhance the health of humans and ecosystems. Data driven models are computing methods that are capable of extracting different system states without using complex relationships. This thesis investigate the capability of an Adaptive Network-Based Fuzzy Inference System as data – driven model to predict and stimulate water quality parameters at Kakrapar station on Tapi River. Building functional relationship between major water quality data (PH ,T,EC,SS,TDS) with one required output water quality parameter (DO, BOD). Selecting best functional relationship among them. At last Comparing observed Water quality data with predicted output and analysis water quality by predicted data. |
Other Details |
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Paper ID: IJSRDV6I21957 Published in: Volume : 6, Issue : 2 Publication Date: 01/05/2018 Page(s): 3291-3295 |
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