The paper presents an approach for evaluation of the likelihood of damage to the transportation infrastructure in the context of the terrorist attacks on the example of a number of bridges located in Wrocław (Poland). Assuming that there will be only one bridge destroyed in a given area, in order to determine the probability of damage to one of the objects, there was one of multi-criteria optimi-zation methods used, i.e. the method of Analytical Hierarchy Process (AHP). The main advantage of the analysis carried out was that the accepted hierarchy of decision-making options could be easily explained in a scientifi c manner, not only with reference to personal knowledge, experience, and intuition.
Overseas mining investment generally faces considerable risk due to a variety of complex risk factors. Therefore, indexes are often based on conditions of uncertainty and cannot be fully quantified. Guided by set pair analysis (SPA) theory, this study constructs a risk evaluation index system based on an analysis of the risk factors of overseas mining investment and determines the weights of factors using entropy weighting methods. In addition, this study constructs an identity-discrepancycontrary risk assessment model based on the 5-element connection number. Both the certainty and uncertainty of the various risks are treated uniformly in this model and it is possible to mathematically describe and quantitatively express complex system decisions to evaluate projects. Overseas mining investment risk and its changing trends are synthetically evaluated by calculating the adjacent connection number and analyzing the set pair potential. Using an actual overseas mining investment project as an example, the risk of overseas mining investment can be separated into five categories according to the risk field, and then the evaluation model is quantified and specific risk assessment results are obtained. Compared to the field investigation, the practicability and effectiveness of the evaluation method are illustrated. This new model combines static and dynamic factors and qualitative and quantitative information, which improves the reliability and accuracy of risk evaluation. Furthermore, this evaluation method can also be applied to other similar evaluations and has a certain scalability.