(My apologies if this thread is too old to respond to - I'm still learning the forum etiquette).
Edited to add: I’m not sure which of the differences between fuzzy and probabilistic uncertainty the OP was already aware of and which he needed more info on, or what types of aggregations he meant, so I’ll just provide a list of some differences I gleaned from Klir and Yuan, off the top of my head.
These include T-norms and T-conorms that are sometimes used in the above calculations of uncertainty.
I can't provide a simple answer, but that's not just due to inexperience - even 20 years after Klir and Yuan wrote, a lot of the math and use cases for things still don’t seem settled.
I hope this edit is of use; if you need more clarification/info, let me know.
Thank you for responding and providing the references.
The risk models is developed using the analytic hierarchy process (AHP) to evaluate risk factors weights (likelihood) and FUZZY LOGIC approach to evaluate risk factors impact (Risk consequences) using software aids such as EXCEL and MATLAB software. Unless the changes are properly controlled, the time, cost and quality goals of the project may never be achieved .
The reliability of the developed software has been tested by applications on a real construction projects. The ability to analyse situations and to make good decisions is a very important aspect of any managerial work.
In other words, if I deal with probabilities (fusing information, aggregating knowledge), can I do the same with FL?
Perhaps you're already aware of this, but Chapters 3, 7 and 9 of George J.
Due to the nature of construction works, there are lots of risks and uncertainties associated with the company and project conditions. It uses a modelling technique based on the Analytical hierarchy Process (Construction projects are exposed to an uncertain environment due to its enormous size (physical, manpower requirement and financial value), complexity in design technology and involvement of external factors.