Georgia Southwestern State University, Americus, GA, USA

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Abstract—A method of modeling human operator performance in complex systems, which is realized as a DSS, is presented. It allows to conduct a detailed analysis of an operator’s performance to observe the nature of his errors in the different stages of his control action: perception of a problem, motivation for solving it, the evaluation of variants of a solution; then, making a decision, and its implementation. The method provides a deeper analysis of underlying factors using the proposed frame descriptions for errors with logical, decision-making, and classification algorithms, as well as the results of psychological experiments. The specific feature of the suggested approach is that it presents the opportunity to logically analyze errors and their underlying factors in the process of collecting data on them, not by drawing conclusions from the investigation reports as the traditional approach. The advantages of using the decision support systems for working with large amounts of unstructured data, specifically in the process of identifying repeated errors and error-provoking situations, are demonstrated.

Index Terms—Operator performance, error, modeling, algorithm for analysis, decision support.

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Cite: Alexander M. Yemelyanov, "Modeling and Decision Support for Analysis of Operator Errors in Complex Systems," Journal of Computers vol. 4, no. 4, pp. 319-329, 2009.