Risk analysis is the analysis of uncertainty of possible natural disasters or the uncertainty of forecasted future cash flows streams, portfolio/stock returns, the probability of a project’s success or failure, and possible future economic states. Risk analysts try to minimize future negative unforeseen effects of these possible events. In recent years, many intelligent techniques and systems have been developed and proposed in the literature. These techniques include fuzzy systems, genetic algorithms, neural networks, Tabu search, ant colony optimization, bee colony optimization, particle swarm optimization, simulated annealing, etc.
The aim of this special issue is to present some research papers with the latest developments on intelligent systems and decision making for risk considerations. We made an open call for papers and 27 papers were submitted for possible publication. After a peer review process, 6 papers were accepted to publish, which means an acceptance ratio of 22%. As the analysis tools, in the six papers of this issue, fuzzy additive multi-attribute utility functions, interval type-2 fuzzy prioritization approaches, multi objective genetic algorithms with fuzzy logic, ANFIS modeling, statistical and machine learning methods, and type-2 fuzzy multi criteria decision making are used.