Efficient wastewater discharge location speculation system based on ensemble classification
by C. Brintha Malar; S. Akilandeswari
International Journal of Advanced Intelligence Paradigms (IJAIP), Vol. 28, No. 3/4, 2024

Abstract: Water pollution is one of the serious threats to the society, as water is the primary need of every organism thriving on earth. It is necessary to control and detect water pollution by assessing the quality of water. However, the production of wastewater is always there and is inevitable. Hence, it is equally important to treat the wastewater in a better way, such that the environment is not affected. The pollution control board has formulated certain standards, which provides the range of values for each pollutant and the feasible discharge locations. Taking these standards as the input for training the system, this work extracts basic statistical features such as mean, standard deviation, entropy and variance for training the classification system. The ensemble classification is incorporated, which includes k-nearest neighbour (k-NN), support vector machine (SVM) and extreme learning machine (ELM). The performance of the proposed approach is evaluated in terms of accuracy, sensitivity and specificity. The results of the proposed approach are found to be satisfactory.

Online publication date: Wed, 24-Jul-2024

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Advanced Intelligence Paradigms (IJAIP):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com