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.

Report Date:

1991-11-01

Pagination or Media Count:

60.0

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