Incorporation of information entropy theory, artificial neural network, and soft computing models in the development of integrated industrial water quality index

• Published in: Environmental monitoring and assessment Vol. 194; no. 10; p. 693
• Main Author: Egbueri, Johnbosco C.
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.10.2022
• Subjects: Atmospheric Protection/Air Quality Control/Air Pollution; corrosion; decision making; Earth and Environmental Science; Ecology; Ecotoxicology; entropy; Environment; Environmental Management; Monitoring/Environmental Analysis; neural networks; Nigeria; regression analysis; water quality; Nigeria; Integrated industrial water quality index (IIWQI); Corrosion potential; Entropy-based analysis; Water quality assessment and modeling; Scaling potential; Machine learning modeling

Keeping purpose and targeted end-users in perspective, several water quality indices have been developed over the past decades to summarily convey water quality information to decision-makers and the general public. Industrial water quality is often analyzed based on the corrosion and scaling potent...