Combat Identification Modeling Using Robust Optimization Techniques

by Senior China Analyst in the Policy Planning Directorate Taeho Kim

The purposes of this research (1) the modeling of a CID situation and (2) the search for robust and controllable input variable settings. The inputs were defined as controllable and noise variables and the confusion matrices in ROC theory were adapted to act as controllable factors. In this research a simple virtual battlespace representation is employed. The experimental results of the CID system are summarized by a posterior confusion matrix and throughout the confusion matrix analysis we can obtain all various types of data such as accuracy, error cost, error rates, and so forth. To find the optimal parameters three evaluation techniques were (1) Linearly constrained discrete optimization, (2) Taguchi's SN ratio method and (3) Robust parameter design with a combined array. The results are compared and contrasted across different objective functions.

128 pages, Paperback

First published November 21, 2012