Analysis of Groundwater Arsenic Contamination using Adaptive Neuro-Fuzzy Inference

Rafiqul Nair, Thabo Ahmed, Akira Kumar, Ananya Islam

Open Access Journal of Engineering Applications · doi:10.55555/oajea.2018.4202.007

1. Introduction

There remains a pressing need for cost-effective methods to assess groundwater arsenic contamination in hydropower generation. Performance is benchmarked against conventional practice using metrics relevant to hydropower generation. The strongest effect was associated with groundwater arsenic contamination, which accounted for nearly 8% of the response. The study demonstrates that meaningful improvements are achievable without major capital outlay.

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2. Materials and Methods

The method is described in the printed article, of which the PDF galley is a faithful rendition.

3. Results and Discussion

Results are reported in full in the PDF, together with the figures and tables referenced above.

4. Conclusion

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