Deep Learning in Water and Environmental Science for Solving Complex Problems

Lorestan University's Growth and Technology Center held a workshop on the application of deep learning models in water and environmental studies, taught by Ms. Leila Ghasemi, a doctoral student in Watershed Science and Engineering at Lorestan University.

According to the Public Relations of Lorestan University, the workshop "Application of Deep Learning Models in Water and Environmental Studies" was held with the aim of familiarizing participants with the "why" and "how" of using deep learning in the field of water and environment, as well as familiarizing them with the transformative power of deep learning in solving complex issues in the field of water and environment, through the demonstration of practical and tangible applications, and encouraging them to utilize this technology in their research and specialized decision-making.

During this two-hour workshop, after a brief review of the necessity and foundations of deep learning, the applications of this technology in three key areas of water and environment (including flood forecasting and water resources management using LSTM, monitoring ecosystem changes with satellite image processing by CNN, water quality prediction, etc.) were examined by providing examples.

In the end, the participants gained a clear understanding of how deep learning can solve complex issues in this field with high accuracy and efficiency, became familiar with its practical challenges, and identified the initial pathways for starting to use this tool in their profession.

Lorestan University's Growth and Technology Center operates under the supervision of the Vice President for Research and Technology of the University.