Desalination of Marine water using Machine Learning Methods

Krishna U. Parvathy, Akhil Krishnan, Mahipal Bukya, Rajesh Kumar, Princy Randhawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Previous works for water desalination usually work for hybrid fault diagonalisation methods. Which has the advantage of improving the dresolution, accuracy and reliability. However, such an assumption is not accurate in certain cases. In this paper, the water desalination fault is detected using the machine learning technique. The proposed method uses the raw data which is obtained from the desalination system. Here machine learning techniques such as deep learning and decision trees were deployed and it was formed that the results obtained from decision trees were more accurate than deep learning.

Original languageEnglish
Title of host publication2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665417037
DOIs
Publication statusPublished - 2021
Event9th IEEE International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2021 - Noida, India
Duration: 03-09-202104-09-2021

Publication series

Name2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2021

Conference

Conference9th IEEE International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2021
Country/TerritoryIndia
CityNoida
Period03-09-2104-09-21

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality
  • Control and Optimization

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