Handbook of Nature-Inspired and Innovative Computing (eBook)

Integrating Classical Models with Emerging Technologies

Albert Y. Zomaya (Herausgeber)

eBook Download: PDF

2006 | 2006
XVI, 736 Seiten
Springer US (Verlag)
978-0-387-27705-9 (ISBN)

Infos

As computing devices proliferate, demand increases for an understanding of emerging computing paradigms and models based on natural phenomena. Neural networks, evolution-based models, quantum computing, and DNA-based computing and simulations are all a necessary part of modern computing analysis and systems development. Vast literature exists on these new paradigms and their implications for a wide array of applications.

This comprehensive handbook, the first of its kind to address the connection between nature-inspired and traditional computational paradigms, is a repository of case studies dealing with different problems in computing and solutions to these problems based on nature-inspired paradigms. The 'Handbook of Nature-Inspired and Innovative Computing: Integrating Classical Models with Emerging Technologies' is an essential compilation of models, methods, and algorithms for researchers, professionals, and advanced-level students working in all areas of computer science, IT, biocomputing, and network engineering.

Albert Zomaya was named an ACM Distinguished Engineer in 2006, at the inception of ACM's program to recognize engineers and scientists for their contributions to both the practical and theoretical aspects of computing and information technology.

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As computing devices proliferate, demand increases for an understanding of emerging computing paradigms and models based on natural phenomena. Neural networks, evolution-based models, quantum computing, and DNA-based computing and simulations are all a necessary part of modern computing analysis and systems development. Vast literature exists on these new paradigms and their implications for a wide array of applications. This comprehensive handbook, the first of its kind to address the connection between nature-inspired and traditional computational paradigms, is a repository of case studies dealing with different problems in computing and solutions to these problems based on nature-inspired paradigms. The "e;Handbook of Nature-Inspired and Innovative Computing: Integrating Classical Models with Emerging Technologies"e; is an essential compilation of models, methods, and algorithms for researchers, professionals, and advanced-level students working in all areas of computer science, IT, biocomputing, and network engineering.

Inhalt

Models.- Changing Challenges for Collaborative Algorithmics.- Arm++: A Hybrid Association Rule Mining Algorithm.- Multiset Rule-Based Programming Paradigm for Soft-Computing in Complex Systems.- Evolutionary Paradigms.- Artificial Neural Networks.- Swarm Intelligence.- Fuzzy Logic.- Quantum Computing.- Enabling Technologies.- Computer Architecture.- A Glance at VLSI Optical Interconnects: from the Abstract Modelings of the 1980s to Today’s MEMS Implementations (A Survey Report).- Morphware and Configware.- Evolving Hardware.- Implementing Neural Models in Silicon.- Molecular and Nanoscale Computing and Technology.- Trends in High-Performance Computing.- Cluster Computing: High-Performance, High-Availability, and High-Throughput Processing on a Network of Computers.- Web Service Computing: Overview and Directions.- Predicting Grid Resource Performance Online.- Application Domains.- Pervasive Computing: Enabling Technologies and Challenges.- Information Display.- Bioinformatics.- Noise in Foreign Exchange Markets.

Produkt-Details

• Erscheint lt. Verlag: 23.3.2006
• Zusatzinfo: XVI, 736 p. 211 illus.
• Verlagsort: New York
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Schlagworte: algorithm • Algorithm analysis and problem complexity • algorithms • Artificial Neural Network • Biocomputing • Bioinformatics • Cluster Computing • Complex System • Computational modeling • distributed algorithms • DNA-based computing • Evolution • fuzzy • Fuzzy Logic • Grid resource performance • Intelligence • Logic • MEMS • microelectromechanical system (MEMS) • Modeling • nanotechnology • Neural models • neural network • Neural networks • Pervasive Computing • programming • Quantum Computing • Simulation • Swarm intelligence • VLSI optical interconnects
• ISBN-10: 0-387-27705-6 / 0387277056
• ISBN-13: 978-0-387-27705-9 / 9780387277059