Weapon Combat Effectiveness Analytics Using Big Data and Simulations: A Literature Review 2019-01-1365
The Weapon Combat Effectiveness (WCE) analytics is very expensive, time-consuming, and dangerous in the real world because we have to create data from the real operations with a lot of people and weapons in the actual environment. The Modeling and Simulation (M&S) of many techniques are used for overcoming these limitations. Although the era of big data has emerged and achieved a great deal of success in a variety of fields, most of WCE research using the Defense Modeling and Simulation (DM&S) techniques studied have considered a lot of assumptions and limited scenarios without the help of big data technologies. Furthermore, WCE analytics using previous methodologies cannot help but get the bias results. This paper reviews and combines the basic knowledge for the new WCE analytics methodology using big data and M&S to overcome these problems of bias. Then this paper reviews the general overview of WCE, DM&S, and big data. Also, it establishes WCE classification and identifies the research challenges and solutions. The new WCE analytics methodology is discussed based on the research solutions. This paper will have a role to further serve as the stepping-stone of the future research for the interested researchers.
Citation: Jung, W., Marin, M., Lee, K., Rabelo, L. et al., "Weapon Combat Effectiveness Analytics Using Big Data and Simulations: A Literature Review," SAE Int. J. Adv. & Curr. Prac. in Mobility 1(2):357-374, 2019, https://doi.org/10.4271/2019-01-1365. Download Citation
Won IL Jung, Mario Marin, Kyungeun Lee, Luis Rabelo, Gene Lee, Daeho Noh
University of Central Florida
SAE International Journal of Advances and Current Practices in Mobility-V128-99EJ