*3.1. Main Assumptions of the Model*

The construction of the cost overrun risk prediction model was based on the fuzzy inference model of Mamdani. This model has been frequently used in the field of construction management, for instance, to build fuzzy risk inference models, in the context of assessing:


A cost overrun risk prediction model is a model with multiple inputs and one output (multi-input-single-output (MISO)), based on processes that run sequentially in three blocks (the fuzzy block, the interference block, and the block of sharpening the representative output value). Share of element costs in the building costs (SE), predicted changes in the number of works (WC), and expected changes in the unit price (PC) are the input variables of the model. The database of 27 individually designed rules supports the inference process in the interference block, and the level of risk of exceeding the costs of a given element of a construction project (R) is an output variable (y).

To construct a cost overrun risk prediction model, the authors decided to choose the theory of possibilities and fuzzy logic, because the risk is related to the so-called measurable uncertainty. Its measurable character results also from the fact that the risk is quantifiable and can be directly translated into the size of parameters necessary, for example, to determine the value of the risk of cost overrun. In practice, it often happens that an expert who evaluates risk does not have a sufficient number of historical data to perform statistical research that would result in a probabilistic distribution, and thus determines subjectively the size of parameters necessary for risk assessment.
