Modeling the level of risk of decisions accepted at management fire elimination

Introduction. Systems of decision-making support, which are applied when managing fire-extinguishing operations, allow reducing direct financial damage and number of dead and wounded. The work in question is devoted to the construction of the risk model based on the decisions taken by the Fire Ground Commander (FGC) being the Decision Maker (DM) in the context of extinguishing the fire in a multi-storey building.

Aims and problems. The objective of the research is the construction of a model that would demonstrate the risk level contained in the decisions of the FGC. In order to achieve the objective it is necessary to solve the following problems: 1) to choose the type of a decision taking model; 2) to build the algorithm of model parameter estimation using the decisions taken by the FGC; 3) to analyze the model's quality.

Methods. The model class called Nature Games has been chosen. The procedure of DM's decision taking process observed while extinguishing the fire in a multi-storey building has been presented as a three-level decision tree. It was transformed into a normal (table) form, thus presenting the decision choice as the Hurwitz Criterion. Hurwitz's parameter of pessimism/optimism demonstrates the risk level contained in the DM's decisions. Simulation modelling has been performed in ordertocheckthe working capacity of the suggested Hurwitz parameter estimation technology.

Results and discussion. Simulation experiments proved the working capacity of the suggested technology on assessingthe DM'sdegreeof risk proneness. The estimates that have been built for different DM allow comparing the risk proneness degree of different FGCs. It provides a possibility to build model estimates based on the decisions taken by the experienced FGC. Estimates of other FGCs thus could be compared with the model ones, drawing conclusions on their management quality.

Conclusion. The objective of the research has been achieved due to solving the set problems. The suggested technology is a high-potential type of machine education that can be used both as a part of the DM's decision taking support systems and when training personnel whose role involves emergency operation control.

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