24th EANN 2023, 14 - 17 June 2023, León, Spain

Conductivity Classification Using Machine Learning Algorithms in the “Bramianon” Dam

Nichat Kiourt, Lazaros Iliadis, Antonios Papaleonidas


  During the "water cycle" process, inorganic as well as organic substances are dissolved, which is completely normal. Organic substances can originate from decaying tree leaves that fall into rivers and lakes, from sewage from living organisms that live in water (e.g. fish) and human waste. Inorganic substances can come from lead and copper in water pipes, from pesticides and generally from various human activities. All these elements contribute to increase of water conductivity. The higher the conductivity in water, the more dangerous it becomes for humans [4]. The purpose of this research is to evaluate and classify water conductivity levels at the “Bramianon” dam of Crete, with the development of powerful Machine Learning models capable of successfully assigning three labels “Low”, “Medium”, “High”.  

*** Title, author list and abstract as seen in the Camera-Ready version of the paper that was provided to Conference Committee. Small changes that may have occurred during processing by Springer may not appear in this window.