Real Time Estimation and Prediction Using Optimistic Simulation and Control Theory Techniques
Jeffrey S. Steinman, Ph.D. WarpIV Technologies, Inc and Timothy Busch, Ph.D., Air Force Research Labs, Rome Labs describe ongoing R&D in a wide variety of use cases that benefit from continuous real-time state estimation to predict future outcomes.
This presentation is an excellent example of the future of complex event processing where the notion of using Kalman Filters for estimation and prediction illustrates one of the operational challenges for folks working in the CEP problem domain.
Example use cases include air traffic control, road congestion, energy grid management, battlespace management, and economic forecasting.
Filed under: Advanced Event Processing, Agents, Analytics, Business Activity Monitoring, Business Event Processing, Business Optimization, Business Process Management, Business Rules, CEP Terminology, CEP Tutorials, Complex Event Processing, Detection Theory, Event Processing, Event Processing Modelling, Modelling and Simulation, Predictive Business, Process Optimization, Scheduling, Security Event Management, Sensor Fusion, Systems Engineering, Use Cases
