Computationally Intelligent Hybrid Systems: The Fusion of by Seppo J. Ovaska

By Seppo J. Ovaska

Content material:
Chapter 1 creation to Fusion of sentimental Computing and tough Computing (pages 5–30): Seppo J. Ovaska
Chapter 2 normal version for Large?Scale Plant program (pages 35–55): Akimoto Kamiya
Chapter three Adaptive Flight regulate: delicate Computing with tough Constraints (pages 61–88): Richard E. Saeks
Chapter four Sensorless keep watch over of Switched Reluctance vehicles (pages 93–124): Adrian David Cheok
Chapter five Estimation of Uncertainty Bounds for Linear and Nonlinear strong keep an eye on (pages 129–164): Gregory D. Buckner
Chapter 6 oblique On?Line device put on tracking (pages 169–198): Bernhard Sick
Chapter 7 Predictive Filtering equipment for energy platforms functions (pages 203–240): Seppo J. Ovaska
Chapter eight Intrusion Detection for machine defense (pages 245–272): Sung?Bae Cho and Sang?Jun Han
Chapter nine Emotion producing approach on Human–Computer Interfaces (pages 277–312): Kazuya Mera and Takumi Ichimura
Chapter 10 advent to clinical info Mining: Direct Kernel tools and purposes (pages 317–362): Mark J. Embrechts, Boleslaw Szymanski and Karsten Sternickel
Chapter eleven world-wide-web utilization Mining (pages 367–396): Ajith Abraham

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Additional resources for Computationally Intelligent Hybrid Systems: The Fusion of Soft Computing and Hard Computing

Example text

P. Vernon, "Systems in Engineering," IEE Review 35, 383-385 (1989). 2. M. Kayton, "A Practitioner's View of System Engineering," IEEE Transactions on Aerospace and Electronic Systems 33, 579-586 (1997). 1 INTRODUCTION Large-scale plants such as chemical, electrical power, and water treatment plants are complex systems, consisting of many interconnected subsystems, subprocesses, or components presenting a wide range of different properties. They can be, for example, linear or nonlinear, well-defined or ill-defined, measurable or unmeasurable, predictable or unpredictable, continuous or discrete, time-variant or timeinvariant, static or dynamic, short-term or long-term, centralized or distributed.

Yoshioka, "Skill-Based PID Control by Using Neural Networks," Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, San Diego, CA, Oct. 1998, pp. 1972-1977. 30. Y. -Y. Chow, "Analysis of Training Neural Compensation Model for System Dynamics Modeling," Proceedings of the International Joint Conference on Neural Networks, Washington, DC, July 2001, pp. 1250-1255. 31. R. Fletcher and M. J. D. Powell, "A Rapidly Convergent Descent Method for Minimization," Computer Journal 6, 163-168 (1963).

Ovaska and H. F. VanLandingham, "Guest Editorial: Special Issue on Fusion of Soft Computing and Hard Computing in Industrial Applications," IEEE Transactions on Systems, Man, and Cybernetics—Part C: Applications and Reviews 32, 69-71 (2002). 9. S. J. Ovaska, H. F. VanLandingham, and A. Kamiya, "Fusion of Soft Computing and Hard Computing in Industrial Applications: An Overview," IEEE Transactions on Systems, Man, and Cybernetics—Part C: Applications and Reviews 32, 72-79 (2002). 10. B. Sick, "Fusion of Hard and Soft Computing Techniques in Indirect, Online Tool Wear Monitoring," IEEE Transactions on Systems, Man, and Cybernetics—Part C: Applications and Reviews 32, 80—91 (2002).

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