Optimal area prediction for waste water discharge by employing supervised learning

Brintha Malar C and Akilandeswari S

Water is the lifeblood of all living beings and hence, this natural resource has to be conserved with all possible efforts. However, due to the increasing trend of urbanization and industrialization, several wastes are produced and are mixed up with water. This causes severe health and sanitation hazard, which should be dealt on time. To regulate this issue, the pollution control board has fixed some standard quality metrics, with which the quality of water can be measured. The pollution control board presets the preferable discharge areas of waste water depending on the quality of the waste water. With this knowledge, this work presents an automatic optimal area prediction system for waste water disposal by employing Extreme Learning Machine (ELM). The ELM is trained with the standards set by the pollution control board and the three classes considered are inland surface water, irrigation and marine coastal areas. The performance of ELM is compared with other classifiers and ELM proves its efficiency in terms of accuracy, sensitivity and specificity rates.

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DOI: http://dx.doi.org/10.24327/ijcar.2017.8526.1378