We propose to compare the performance of a parallel distributed processing system with an operational time series model to predict mean length of service (LOS) in a military personnel system After testing a simple model to gauge the suitability of neural networks for pattern recognition, various standard network types were tested, including Adaline, counterpropagation, and backpropagation. The networks are being tested to see if they can provide forecasts that are more sensitive to turning point fluctuations than standard time series models Keywords: neural nets, forecasting, time series analysis
Get full access to this article
View all access options for this article.
References
1.
Ahmadi, H. (1990) Testability of the arbitrage pricing theory by neural nets In Maureen Caudill (Ed.), Proceedings of the International Joint Conference on Neural Networks (p. I-385). Hillsdale, NJ: Lawrence Erlbaum Associates.
2.
Armstrong, J. (1978). Long range forecasting From crystal ball to computer.New York. Wiley.
3.
Chipman, [first name unknown]. (1977) Forecasting the naval enlisted personnel force structure to estimate basic payNavy Personnel Research and Development Center.
4.
Kamijo, K., & Tomigawa, T. (1990). Stock price recognition A recurrent neural network approach In Maureen Caudill (Ed.), Proceedings of the International Joint Conference on Neural Networks (p. I-215). Hillsdale, NJ: Lawrence Erlbaum Associates.
5.
Kimoto, T., Asakawa, K., Yoda, M., & Takeoka, M. (1990). Stock market prediction system with modular neural networks In Maureen Caudill (Ed.), Proceedings of the International Joint Conference on Neural Networks (p. I-1). Hillsdale, NJ: Lawrence Erlbaum Associates.
6.
Klimasauskas, C. (1988). NeuralWorks user's guidePittsburgh: NeuralWare.
7.
Levenbach, H., & Cleary, J. (1984). The modern forecaster: The forecasting process through data analysisBelmont, CA: Lifetime Learning Publications.
8.
McMahon, D.C. (1990). A neural network trained to select aircraft maneuvers during air combat: A comparison of network and rule-based performance In Maureen Caudill (Ed.), Proceedings of the International Joint Conference on Neural Networks (p. I-107). Hillsdale, NJ : Lawrence Erlbaum Associates.
Odom, M.D., & Sharda, R. (1990). A neural network model for bankruptcy prediction In Maureen Caudill (Ed.), Proceedings of the International Joint Conference on Neural Networks (p. II-163). Hillsdale, NJLawrence Erlbaum Associates.
11.
McClelland, J., & Rumelhart, D. (1986) Parallel distributed processing (vol. 1). Cambridge : MIT Press.
12.
Veezhinathan, J., & Wagner, D. (1990). A neural network approach to first break pricing In Maureen Caudill (Ed.), Proceedings of the Joint International Conference on Neural Networks (p. I-325) Hillsdale, NJ: Lawrence Erlbaum Associates.
