AI4CC 2024 - Program

Program

November 28th, 2024

Room F0.03

(15min Talk + 5 min Questions)

[10:30 - 12:30] Session 1

Chair: Diego Aineto

[10:30-10:50] -- What’s Behind This Water Table Depth Forecasting? RISE Application for Spatial, Temporal, and Spatio-Temporal Explanations, Matteo Salis, Gabriele Sartor, Rosa Meo, Marco Pellegrino, Stefano Ferraris, Abdourrahmane Atto.
[10:50-11:10] -- Evaluation of Machine Learning Techniques for Inflow Prediction in Lake Como, Italy, Michele Pini, Andrea Scalvini, Muhammad Usman Liaqat, Roberto Ranzi, Ivan Serina, Tahir Mehmood
[11:10-11:30] -- An Artificial Intelligence Approach for Multi-(hazard-)risk Assessment on River Water Quality under Changing Climate, Diep N Nguyen, Jacopo Furlanetto, Silvia Torresan, Andrea Critto.
[11:30-11:50] --Urban Heat Island. Machine Learning Models for Analysis and Maker Approach for Mitigation, Ermanno Zuccarini.
[11:50-12:10] -- Development of Fuzzy Logic Based Meteorological Drought Index, Mhamd Saifaldeen Oyounalsoud, Abdullah Gokhan Yilmaz, Mohamed Abdallah, Serter Atabay.
[12:10-12:30] -- Semantic Segmentation for Agricultural Land Cover Mapping: A Comparative Study Using Deep Learning and Pre-Trained Models, Girma Tariku Woldesemayat.

[12:30 - 13:30] Lunch

[15:30 - 16:00] Coffee Break

[16:00 - 16:40] Keynote Speaker

Chair: Ivan Serina

Multi-Purpose Resevoir Optimization using Genetic Algorithms for the Hoa Binh Reservoir, Viet Nam -- Roberto Ranzi and Hai Yen Nguyen, University of Brescia Italy.

This talk analyses the use of the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to optimise the operational management of the multi-purpose Hoa Binh Reservoir, located in northern Vietnam. This reservoir has a key role in the region’s water resource management, contributing to water supply, energy production, and flood control. The primary focus of this analysis is on optimising the reservoir’s operation during the dry season, when water availability is limited, and operational conflicts intensify. During this period, there is a conflict between two major objectives: releasing sufficient water to meet downstream demand in the Red River Delta and maintaining an appropriate reservoir elevation to maximise hydroelectric power generation. Using NSGA-II, this study seeks to identify the optimal operational strategies that satisfy both the downstream water supply requirements and the reservoir’s electricity generation potential. Over the period from 2001 to 2010, the study demonstrates that it is possible to increase electricity production by an average of 11% without compromising the necessary water releases to the Delta region.

[16:40-17:40] Session 2

Chair: Ivan Serina

[16:40-17:00] -- Leveraging AI Planning Models for the Water Management of the Red River Basin in Vietnam, Diego Aineto, Matteo Battisti, Hai Yen Nguyen, Ngo Le An, Roberto Ranzi, Enrico Scala, Ivan Serina.
[17:00-17:20] -- Assessing the Impact of Climate Change on Mineral-Associated Organic Carbon (MAOC) Using Machine Learning Models, Tewabe Chekole Workneh, Matteo Cristani, Claudio Tomazzoli.
[17:20-17:40] -- A Novel Methodology for AI-based Sorting of Post-Consumer Textile Using Spectrophotometer, Megan Robinson, Saikat Ghosh, Parikshit Goswami, Mauro Vallati.

[17:40 - 18:00] Closing Remarks

Chair: Ivan Serina

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