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Integrating Soft Set Theory and Fuzzy Linguistic Model to Evaluate the Performance of Training Simulation Systems

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  • Kuei-Hu Chang
  • Yung-Chia Chang
  • Kai Chain
  • Hsiang-Yu Chung

Abstract

The advancement of high technologies and the arrival of the information age have caused changes to the modern warfare. The military forces of many countries have replaced partially real training drills with training simulation systems to achieve combat readiness. However, considerable types of training simulation systems are used in military settings. In addition, differences in system set up time, functions, the environment, and the competency of system operators, as well as incomplete information have made it difficult to evaluate the performance of training simulation systems. To address the aforementioned problems, this study integrated analytic hierarchy process, soft set theory, and the fuzzy linguistic representation model to evaluate the performance of various training simulation systems. Furthermore, importance–performance analysis was adopted to examine the influence of saving costs and training safety of training simulation systems. The findings of this study are expected to facilitate applying military training simulation systems, avoiding wasting of resources (e.g., low utility and idle time), and providing data for subsequent applications and analysis. To verify the method proposed in this study, the numerical examples of the performance evaluation of training simulation systems were adopted and compared with the numerical results of an AHP and a novel AHP-based ranking technique. The results verified that not only could expert-provided questionnaire information be fully considered to lower the repetition rate of performance ranking, but a two-dimensional graph could also be used to help administrators allocate limited resources, thereby enhancing the investment benefits and training effectiveness of a training simulation system.

Suggested Citation

  • Kuei-Hu Chang & Yung-Chia Chang & Kai Chain & Hsiang-Yu Chung, 2016. "Integrating Soft Set Theory and Fuzzy Linguistic Model to Evaluate the Performance of Training Simulation Systems," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-29, September.
    • Handle: RePEc:plo:pone00:0162092
    DOI: 10.1371/journal.pone.0162092
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    1. Iraklis Kollias & John Leventides & Vassilios G. Papavassiliou, 2024. "On the solution of games with arbitrary payoffs: An application to an over‐the‐counter financial market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1877-1895, April.
    2. Kuei-Hu Chang & Yi-Jun Chen & Chung-Cheng Liao, 2024. "A novel improved FMEA method using data envelopment analysis method and 2-tuple fuzzy linguistic model," Annals of Operations Research, Springer, vol. 341(1), pages 485-507, October.
    3. Kuei-Hu Chang, 2019. "A novel supplier selection method that integrates the intuitionistic fuzzy weighted averaging method and a soft set with imprecise data," Annals of Operations Research, Springer, vol. 272(1), pages 139-157, January.
    4. Kuei-Hu Chang, 2022. "A novel reliability calculation method under neutrosophic environments," Annals of Operations Research, Springer, vol. 315(2), pages 1599-1615, August.

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