Abstract. A rough method for estimating commanding efficiency of Fire&Rescue officers is presented in the article. The idea is to evaluate the officers in charge and their actions based on the information collected in the incident data reporting system. The criteria for the commanding evaluation is the distribution of durations of the actions conducted by consecutive commanders.
Abstract-The paper shows the application of election algorithms in networks of comparators. We have described and adopted six election methods which have been used as an aggregator of partial results. We have performed experiments on the data gathered at the fire ground. All of them have been well described and results have been compared. The paper includes a discussion and interpretation of results obtained. It indicates the algorithm with the greatest potential to adapt and to obtain the best results.
A platform for fire & rescue incident data reporting system (IDRS) is presented as an example how the domain knowledge driven granule formation can assist in knowledge discovery and decision support. The current modeling, monitoring and reporting systems rarely take advantage of semantic background of the analyzed phenomena. We discuss how to build and tune practically meaningful models of processes by means of granules approximating their states and instances. We show how the layers of model creation should interact with lower-level layers of data preparation and transformation. We illustrate the proposed methodology by several IDRS related use cases. We also discuss the complexity of available data sources that can be utilized to make the proposed approach more useful.
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