Accession Number : ADA243802


Title :   Neural Networks and Their Application to Air Force Personnel Modeling


Descriptive Note : Final rept. Sep 1989-May 1991


Corporate Author : RRC INC BRYAN TX


Personal Author(s) : Wiggins, Vince L ; Looper, Larry T ; Engquist, Sheree K


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a243802.pdf


Report Date : Nov 1991


Pagination or Media Count : 60


Abstract : Neural network technology has recently demonstrated capabilities in areas important to personnel research such as statistical analysis, decision modeling, control, and forecasting. The present investigation indicates that three different neural network architectures are particularly suited to modeling many aspects of the Air Force personnel system: back propagation, learning vector quantization, and probabilistic neural networks. The primary advantage of neutral networks is their ability to derive nonlinear and interacting relationships among model variables. Two areas investigated in order to evaluate this capability were airmen reenlistment decisions and airman inventory modeling.


Descriptors :   *PROPAGATION , NEURAL NETS , DECISION MAKING , MODELS , NETWORKS , PERSONNEL MANAGEMENT , INTERACTIONS , NEUTRAL , PROBABILITY , VARIABLES , AIR FORCE PERSONNEL , NONLINEAR SYSTEMS , VECTOR ANALYSIS , QUANTIZATION , INVENTORY , PERSONNEL , STATISTICAL ANALYSIS , ARCHITECTURE , LEARNING , AVIATION PERSONNEL , REENLISTMENT


Subject Categories : Personnel Management and Labor Relations
      Operations Research
      Computer Programming and Software


Distribution Statement : APPROVED FOR PUBLIC RELEASE