Implementation of Decision Support Method Based on JCH Standards
The use of modern computer systems in epidemiological centers has become very popular in recent years. The development of mathematical models and IT tools has accelerated making accurate decisions based on real data. The paper presents the use of JCH formulas for graphic representation of modeling patterns of epidemiological disease units in a computer system. Additionally, the general concept of a method for supporting the client's threat detection process was presented based on the similarity of the model contained in the repository of specimens of epidemiological units. The method is based on the distance of Minkowski, using methods (state) of inference based on the definition of similarity, between the normal state of the environment and the emerging epidemiological threats. Similar methods are ARAS, T \ TMP in ALS methods. These methods consist in taking into account the validity of the criteria, i.e. determining the criteria validity coefficients. The aim of the implementation was to create a ranking of symptom importance and risk factors occurring at epidemiological centers based on JCH patterns. The developed method supports the detection of epidemiological threats by searching as much as possible of the Pareto Optimal area from the search criteria. The defined method is part of the algorithm supporting decontamination of threats using multi-criteria optimization methods.
Keywords - JCH standards, pattern recognition, optymalization