Quantum Inspired Intelligent Systems [electronic resource] / edited by Nadia Nedjah, Leandro dos Santos Coelho, Luiza de Macedo Mourelle.

By: Nedjah, Nadia [editor.]Contributor(s): Coelho, Leandro dos Santos [editor.] | Mourelle, Luiza de Macedo [editor.] | SpringerLink (Online service)Material type: TextTextLanguage: English Series: Studies in Computational Intelligence: 121Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008Description: XIV, 156 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783540785323Subject(s): Engineering | Artificial intelligence | Quantum theory | Engineering mathematics | Engineering | Appl.Mathematics/Computational Methods of Engineering | Artificial Intelligence (incl. Robotics) | Quantum Physics | Quantum Information Technology, SpintronicsAdditional physical formats: Printed edition:: No titleDDC classification: 519 LOC classification: TA329-348TA640-643Online resources: Click here to access online
Contents:
Gaussian Quantum-Behaved Particle Swarm Optimization Applied to Fuzzy PID Controller Design -- Quantum-inspired genetic algorithms for flow shop scheduling -- Quantum Simulataneous Recurrent Networks for Content Addressable Memory -- Quantum Intelligent Mobile System -- Quantum Associative Pattern Retrieval -- Quantum-Inspired Evolutionary Algorithm for Numerical Optimization -- Calibration of the VGSSD Option Pricing Model using a Quantum-inspired Evolutionary Algorithm.
In: Springer eBooksSummary: Research on applying principles of quantum computing to improve the engineering of intelligent systems has been launched since late 1990s. This emergent research field concentrates on studying on quantum computing that is characterized by certain principles of quantum mechanics such as standing waves, interference, quantum bits, coherence, superposition of states, and concept of interference, combined with computational intelligence or soft computing approaches, such as artificial neural networks, fuzzy systems, evolutionary computing, swarm intelligence and hybrid soft computing methods. This volume offers a wide spectrum of research work developed using soft computing combined with quantum computing systems.
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Gaussian Quantum-Behaved Particle Swarm Optimization Applied to Fuzzy PID Controller Design -- Quantum-inspired genetic algorithms for flow shop scheduling -- Quantum Simulataneous Recurrent Networks for Content Addressable Memory -- Quantum Intelligent Mobile System -- Quantum Associative Pattern Retrieval -- Quantum-Inspired Evolutionary Algorithm for Numerical Optimization -- Calibration of the VGSSD Option Pricing Model using a Quantum-inspired Evolutionary Algorithm.

Research on applying principles of quantum computing to improve the engineering of intelligent systems has been launched since late 1990s. This emergent research field concentrates on studying on quantum computing that is characterized by certain principles of quantum mechanics such as standing waves, interference, quantum bits, coherence, superposition of states, and concept of interference, combined with computational intelligence or soft computing approaches, such as artificial neural networks, fuzzy systems, evolutionary computing, swarm intelligence and hybrid soft computing methods. This volume offers a wide spectrum of research work developed using soft computing combined with quantum computing systems.

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