Handbook of Bioinspired Algorithms and Applications (eBook, PDF)

Redaktion: Olariu, Stephan; Zomaya, Albert Y.

• Format: PDF

Produktbeschreibung

The mystique of biologically inspired (or bioinspired) paradigms is their ability to describe and solve complex relationships from intrinsically very simple initial conditions and with little or no knowledge of the search space. Edited by two prominent, well-respected researchers, the Handbook of Bioinspired Algorithms and Applications reveals the

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 704
• Erscheinungstermin: 29. September 2005
• Englisch
• ISBN-13: 9781420035063
• Artikelnr.: 52920425

Autorenporträt

Stephan Olariu, Albert Y. Zomaya

Inhaltsangabe

MODELS AND PARADIGMS. Evolutionary Algorithms. An Overview of Neural
Networks Models. Ant Colony Optimization. Swarm Intelligence. Parallel
Genetic Programming: Methodology, History, and Application to Real Life
Problems. Parallel Cellular Algorithms and Programs. Decentralized Cellular
Evolutionary Algorithms. Optimization Via Gene Expression Algorithms.
Dynamic Updating DNA Computing Algorithms. A Unified View on Metaheuristics
and Their Hybridization. The Foundations of Autonomic Computing.
APPLICATION DOMAINS. Setting Parameter Values for Parallel Genetic
Algorithms: Scheduling Tasks on a Cluster. Genetic Algorithms for
Scheduling in Grid Computing Environments: A Case Study. Minimization of
SADMs in Unidirectional SONET/WDM Rings Using Genetic Algorithm. Solving
Optimization Problems in Wireless Networks Using Genetic Algorithms.
Medical Imaging and Diagnosis Using Genetic Algorithms. Multiprocessor
Scheduling and Rescheduling with Use of Cellular Automata. Cellular
Automata, PDEs, and Pattern Formation. Ant Colonies and the Mesh
Partitioning Problem. Simulating the Strategic Adaptation of Organizations
Using OrgSwarm. BeeHive: New Ideas for Developing Routing Algorithms
Inspired by Honey Bee Behavior. Swarming Agents for Decentralized
Clustering in Spatial Data. Biological Inspired Based Intrusion Detection
Models for Mobile Telecommunication Systems. Synthesis of Multiple-Valued
Circuits by Neural Networks. On the Computing Capacity of Multiple-Valued
Multiple Threshold Perceptrons. Advanced Evolutionary Algorithms for
Training Neural Networks. Bio-Inspired Data Mining. A Hybrid Evolutionary
Algorithm for Knowledge Discovery in Microarray Experiments. Evolutionary
Approach to Electrical Engineering Design Problems. Solving the
Partitioning Problem in Distributed Virtual Environment Systems Using
Evolutive Algorithms. Population Learning Algorithm and Its Applications.
Biology-Derived Algorithm in Engineering Optimization. Biomimetic Models
for Wireless Sensor