Applied AI for predicting the quality of irrigation services in the Red river delta
To predict the satisfaction of users who use the water services is very important for the fee exemption policy to water and agriculture services. This policy has positive impacts on the water exploited and management enterprises, the national budget and social security. In this talk, some machine learning models are presented to predict the satisfaction of users related to the quality of irrigation service in the red river delta. Experimental results showed that the non-linear machine learning models achieve lower regression errors than linear models, these linear models are commonly used by irrigation experts. The diversity and feasibility of these machine learning models can be applied for dealing with economic problems in the domain of water resource management.
Dr. Nguyen Thanh Tung – Thuyloi University (Vietnam)
Tung Nguyen received his BS and MSc. degree in Information Technology from Vietnam National University (Hanoi) and a PhD. in Computer Applied Technology from Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China. He has worked as a lecturer, researcher, consultant positions related to data management and mining for more than 20 years. He has been a visiting researcher at Vietnam Institute for Advanced Study in Mathematics (VIASM), big data institute-Shenzhen University in China (2015), Machine learning and Robot Lab, Department of Computer Science, SUSTech and Center for Automata Processing, Department of Computer Science, University of Virginia.
His current research interests include Artificial intelligence, Machine learning and Data mining, especially advanced machine learning methods for the problems of classification; statistical learning, regression ensemble methods for high-dimensional data. He has published around 20 papers in international journals and conference proceedings in these areas.