Neural networks as a tool for developing and validating business heuristics

Expert Systems with Applications

Volumn 21, Issue 1, 2001, Pages 31-36

  Walczak, Steven ^a  

^a UNIVERSITY OF COLORADO   (United States)

Author keywords

Empirical evaluation; Heuristics; Model selection; Neural networks

Indexed keywords

COMPUTER SOFTWARE SELECTION AND EVALUATION; DECISION MAKING; HEURISTIC METHODS; MATHEMATICAL MODELS; NEURAL NETWORKS;

EMPIRICAL EVALUATION;

COMPUTER AIDED SOFTWARE ENGINEERING;

EID: 0035399150     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0957-4174(01)00024-0     Document Type: Article

References (25)

1. Comparing the modeling performance of regression and neural networks as data quality varies: A business value approach
2. A comparison of statistical and connectionist models for the prediction of chronicity in a surgical intensive care unit
3. Artificial neural networks in pathology and medical laboratories
4. Approximation capabilities of multilayer feedforward networks
5. Multilayer feedforward networks are universal approximators
6. A cross-validation analysis of neural network out-of-sample performance in exchange rate forecasting
7. Determining the saliency of input variables in neural network classifiers
8. Specifying critical inputs in a genetic algorithm-driven decision support system: An automated facility
9. Use of an artificial neural network to predict length of stay in acute pancreatitis
10. A classification approach using multi-layered neural networks
11. Etiological and prognostic factors in human acute pancreatitis: A review
12. A Model-Selection approach to assessing the information in the term structure using linear models and artificial neural networks
13. Improving artificial neural network performance through input variable selection
14. Developing neural nets for currency trading
15. Information effects on the accuracy of neural network financial forecasting
16. An empirical analysis of data requirements for financial forecasting with neural networks
17. Heuristic principles for the design of artificial neural networks
18. Improved cash flows using neural network models for forecasting foreign exchange rates
19. Analyzing intensive care unit length of stay data: Problems and possible solutions
20. Connectionist nonparametric regression: Multilayer feedforward networks can learn arbitrary mappings