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

• Published in: PloS one 2016-09, Vol.11 (9), p.e0162092-e0162092
• Main Authors: Chang, Kuei-Hu, Chang, Yung-Chia, Chain, Kai, Chung, Hsiang-Yu
• Format: Article
• Language: English
• Subjects: Analytic hierarchy process; Aviation; Biology and Life Sciences; Computer and Information Sciences; Computer simulation; Computers; Cost analysis; Decision making; Drills; Engineering and Technology; Fuzzy Logic; Fuzzy set theory; Fuzzy sets; Fuzzy systems; High Fidelity Simulation Training - economics; High Fidelity Simulation Training - methods; Humans; Industrial engineering; Information technology; Linguistic research; Linguistics; Mathematical models; Mathematical problems; Medicine and Health Sciences; Military; Military Personnel - education; Military Personnel - psychology; Military preparedness; Military training; Network security; Performance evaluation; Physical Sciences; Pilots; Ranking; Research and Analysis Methods; Set theory; Simulation; Simulators (Training equipment); Software; Suppliers; Training; Warfare
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0162092

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.