Workshop 1
Summary:
In the context of the rapid development of global informatization, big data has become a strategic resource. The frequency, breadth, and complexity of decision-making activities in various industries are fundamentally different from before. The uncertainty factors in the decision-making process increase, and the difficulty of decision-making analysis continues to increase. Traditional data analysis methods and decision-making based on human experience are no longer able to meet the decision-making needs of the big data era, Big data-driven intelligent decision-making will become the main theme of decision-making research. We need to combine the characteristics of big data and analyze some potential research directions from aspects such as intelligent decision support systems, uncertainty processing, information fusion, correlation analysis, and incremental analysis. As a rapidly developing open discipline, big data intelligent decision-making still requires more research and practice in terms of connotation and extension, model theory, technical methods, and implementation strategies.
Keywords: big data, intelligent decision-making, information fusion, incremental learning
Xin NIE is a professor and master's supervisor at the School of Computer Science and Engineering, Wuhan Institute of Technology. His research interests include intelligent optimization algorithms, machine vision, and other fields. He is currently the director of the Software Engineering Teaching and Research Office, a member of the China Computer Society, a member of the China Artificial Intelligence Society, and a member of the China Command and Control Committee.