3.3 Systems Modelling, Analysis, and Decision Making under uncertainty

Nature and human society are full of uncertainties. Just as Professor Robert Vallée, former president of WOSC, said that “Greyness is the field we live in”...

  Nature and human society are full of uncertainties. Just as Professor Robert Vallée, former president of WOSC, said that “Greyness is the field we live in”. Uncertainty plays a significant role in the world. The interactions between technology and people in society are indeed complicated and traditional mathematical systems have no capacity to model them. Alternative systems are necessary to model such interactions, among them, data-driven models are gaining momentum.

 

  With the increased availability of data from Internet and the Internet of things (IOT), big data technology is the current focus for such developments.  However, uncertainty in systems means that the historical data cannot reflect recent changes of policy or other environment factors, and the only reliable data is likely to be real time data rather than historical big data.  And, of course unexpected uncertainty can always surprise us in modelling.

  Therefore, effective modelling, maximizing the use of available meaningful, albeit limited data, recognizing uncertainties is essential in our big data age. Among others, the theory of grey systems does provide exactly such a facility (Sifeng Liu, Yingjie Yang).  Here, this session, wants to highlight the role of grey systems; this debate will focus mainly on the two extremes: big data and limited data, certainty and uncertainty.

Discussion points

  • Data Mining and Processing

  • Systems Modelling and Simulation

  • Forecasting and Decision Making

  • Uncertainty Control

  • Relation Analysis Model

  • Clustering Evaluation

  • Complex Equipment Development Management

  • Technical Innovation and Emerging Industry Development

  • Computational Intelligence

  • Uncertainty Analysis and Applications

Coordinators