About this document
Optimize Drinking Water with ML & Graph Theory by phuckhanglg20030316 is a document available to read on EtoBox.
This document discusses the optimization of drinking water distribution networks through the use of machine learning and graph theory to determine the optimal placement of rechlorination stations. It highlights the challenges of maintaining chlorine levels in the network and compares two approaches: dynamic programming and graph theory, with findings indicating that graph theory offers improved response times. The study includes performance tests conducted on real sites in Rabat-Sale, Morocco, demonstrating
- Author
- phuckhanglg20030316
- Language
- EN