A knowledge-based assignment methodology for personal identification in mass disaster

A knowledge-based assignment methodology (KBAM) for providing decision support to forensic scientists in the skeletal identification process is discussed. A mathematical framework for KBAM is developed that integrates a knowledge base with a network flow algorithm to resolve conflicts during the identification process. The KBAM framework has been implemented on an IBM-PC and includes an observation advisor, an assignment advisor and a conflict resolution module. Knowledge acquisition and representation issues are discussed along with a numerical example and results.