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Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17

C. H. Dagli
C. H. Dagli
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ASME Press
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Artificial intelligent systems can learn to adapt to environmental changes to find a better solution. Improving system performance has been a great interest of study with new objective functions and parameters being constantly applied. However, approaches for performance evaluation are often by real observation without offering a prediction capability to support decision making at run time. Prediction helps foresee the future, so that a good run can continue while a poor one can be replaced. It also assists in evaluating the efficacy of different algorithms, especially when their learning capabilities vary over time. In this paper, a statistical approach is...

1. Introduction
2. Methodology
3. A Case Study
4. Conclusion
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