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Innovations in Intelligent Machines-5 [electronic resource] : Computational Intelligence in Control Systems Engineering / edited by Valentina Emilia Balas, Petia Koprinkova-Hristova, Lakhmi C. Jain.

Contributor(s): Balas, Valentina Emilia [editor.] | Koprinkova-Hristova, Petia [editor.] | Jain, Lakhmi C [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Studies in Computational Intelligence: 561Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014Description: XV, 248 p. 129 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783662433706.Subject(s): Engineering | Artificial intelligence | Computational intelligence | Control engineering | Engineering | Computational Intelligence | Control | Artificial Intelligence (incl. Robotics)Additional physical formats: Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
Decentralized Fuzzy-Neural Identification and I-Term Adaptive Control of Distributed Parameter Bioprocess Plan -- Error Tolerant Predictive Control based on Recurrent Neural Models -- Advances in Multiple Models based Adaptive Switching Control: from Conventional to Intelligent approaches -- A Computational Intelligence Approach to Software Component Repository Management -- A Soft Computing Approach to Model Human Factors in Air Warfare Simulation System -- Application of Gaussian Processes to the Modelling and Control in Process Engineering -- Computational Intelligence Techniques for Chemical Process Control -- Application of Swarm Intelligence in Fuzzy Entropy based Image Segmentation.
In: Springer eBooksSummary: This research monograph presents selected areas of applications in the field of control systems engineering using computational intelligence methodologies. A number of applications and case studies are introduced. These methodologies are increasing used in many applications of our daily lives. Approaches include, fuzzy-neural multi model for decentralized identification, model predictive control based on time dependent recurrent neural network development of cognitive systems, developments in the field of Intelligent Multiple Models based Adaptive Switching Control, designing military training simulators using modelling, simulation, and analysis for operational analyses and training, methods for modelling of systems  based on the application of Gaussian processes, computational intelligence techniques for process control and image segmentation technique based on modified particle swarm optimized-fuzzy entropy.
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Decentralized Fuzzy-Neural Identification and I-Term Adaptive Control of Distributed Parameter Bioprocess Plan -- Error Tolerant Predictive Control based on Recurrent Neural Models -- Advances in Multiple Models based Adaptive Switching Control: from Conventional to Intelligent approaches -- A Computational Intelligence Approach to Software Component Repository Management -- A Soft Computing Approach to Model Human Factors in Air Warfare Simulation System -- Application of Gaussian Processes to the Modelling and Control in Process Engineering -- Computational Intelligence Techniques for Chemical Process Control -- Application of Swarm Intelligence in Fuzzy Entropy based Image Segmentation.

This research monograph presents selected areas of applications in the field of control systems engineering using computational intelligence methodologies. A number of applications and case studies are introduced. These methodologies are increasing used in many applications of our daily lives. Approaches include, fuzzy-neural multi model for decentralized identification, model predictive control based on time dependent recurrent neural network development of cognitive systems, developments in the field of Intelligent Multiple Models based Adaptive Switching Control, designing military training simulators using modelling, simulation, and analysis for operational analyses and training, methods for modelling of systems  based on the application of Gaussian processes, computational intelligence techniques for process control and image segmentation technique based on modified particle swarm optimized-fuzzy entropy.

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