Rapid learning applications. Contrasts with alternative methods. The rapid learning neuro-computing system. Rapid learning models. Basic concurrent learning and prediction. Extended concurrent learning and prediction. Monitoring and forecasting details. Control and refinement details. Glossary. Index.
Many monitoring, forecasting, and control operations occur in settings where relationships among key measurements must be learned quickly. Examples are on-line industrial processes where influent material is not consistent over time, energy load or price forecasting where demand characteristics change rapidly,and health management where relationships among monitored variables must be learned for each patient-treatment combination. The solution presented is a new neuro-computing system that learns in real-time, even when data arrival rates are several million measurements per second. The book describes benefits and features of the system, statistical foundations for the system, and several related models.
The book also describes available system software.
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