Handbook of Bioinspired Algorithms and Applications
eBook - PDF

Handbook of Bioinspired Algorithms and Applications

  1. 704 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Handbook of Bioinspired Algorithms and Applications

About this book

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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Yes, you can access Handbook of Bioinspired Algorithms and Applications by Stephan Olariu, Albert Y. Zomaya, Stephan Olariu,Albert Y. Zomaya in PDF and/or ePUB format, as well as other popular books in Computer Science & Programming Algorithms. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Preface
  2. Acknowledgments
  3. Editors
  4. Contributors
  5. Contents
  6. 1 Evolutionary Algorithms
  7. 2 An Overview of Neural Networks Models
  8. 3Ant ColonyOptimization
  9. 4 Swarm Intelligence
  10. 5 Parallel Genetic Programming: Methodology, History,and Application to Real-Life Problems
  11. 6 Parallel Cellular Algorithms and Programs
  12. 7 Decentralized Cellular Evolutionary Algorithms
  13. 8 Optimization via Gene Expression Algorithms
  14. 9 Dynamic Updating DNA Computing Algorithms
  15. 10 A Unified View on Metaheuristics and Their Hybridization
  16. 11 The Foundations of Autonomic Computing
  17. 12 Setting Parameter Values for Parallel Genetic Algorithms: Scheduling Tasks on a Cluster
  18. 13 Genetic Algorithms for Scheduling in Grid Computing Environments: A Case Study
  19. 14 Minimization of SADMs in Unidirectional SONET/WDM Rings Using Genetic Algorithms
  20. 15 Solving Optimization Problems in Wireless Networks Using Genetic Algorithms
  21. 16 Medical Imaging and Diagnosis Using Genetic Algorithms
  22. 17 Scheduling and Rescheduling with Use of Cellular Automata
  23. 18 Cellular Automata, PDEs, and Pattern Formation
  24. 19 Ant Colonies and the Mesh-Partitioning Problem
  25. 20 Simulating the Strategic Adaptation of Organizations Using OrgSwarm
  26. 21 BeeHive: New Ideas for Developing Routing Algorithms Inspired by Honey Bee Behavior
  27. 22 Swarming Agents for Decentralized Clustering in Spatial Data
  28. 23 Biological Inspired Based IntrusionDetection Modelsfor MobileTelecommunicationSystems
  29. 24 Synthesis of Multiple-Valued Circuits by Neural Networks
  30. 25 On the Computing Capacity of Multiple-Valued Multiple-Threshold Perceptrons
  31. 26 Advanced Evolutionary Algorithms for Training Neural Networks
  32. 27 Bio-Inspired Data Mining
  33. 28 A Hybrid Evolutionary Algorithm for Knowledge Discovery in Microarray Experiments
  34. 29 An Evolutionary Approach to Problems in Electrical Engineering Design
  35. 30 Solving the Partitioning Problem in Distributed Virtual Environment Systems Using Evolutive Algorithms
  36. 31 Population Learning Algorithm and Its Applications
  37. 32 Biology-Derived Algorithms in Engineering Optimization
  38. 33 Biomimetic Models for Wireless Sensor Networks
  39. 34 A Cooperative Parallel Metaheuristic Applied to the Graph Coloring Problem
  40. 35 Frameworks for the Design of Reusable Parallel and Distributed Metaheuristics
  41. 36 Parallel Hybrid Multiobjective Metaheuristics on P2P Systems
  42. Back Cover