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Nature-Inspired Computing Design, Development, and Applications

Book Description

The observation of nature has been the inspiration for many materials, laws, and theories, as well as computational methods.Nature-Inspired computing Design, Development, and Applications covers all the main areas of natural computing, from methods to computationally synthesized natural phenomena, to computing paradigms based on natural materials. This volume is comprised of ideas and research from nature to develop computational systems or materials to perform computation. Researchers, academic educators, and professionals will find a comprehensive view of all aspects of natural computing with emphasis on its main branches.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Editorial Advisory Board and List of Reviewers
    1. Editorial Advisory Board
  5. Preface
    1. 1. INSPIRING, SYNTHESIZING, COMPUTING … AND MODELING
    2. 2. NATURAL COMPUTING: FROM DISCIPLINE TO SCIENCE
    3. 3. THE INTERNATIONAL JOURNAL OF NATURAL COMPUTING RESEARCH
  6. Chapter 1: Conceptual and Practical Aspects of the aiNet Family of Algorithms
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. NATURAL AND ARTIFICIAL IMMUNE SYSTEMS
    4. 3. THE ARTIFICIAL IMMUNE NETWORK ALGORITHM – aiNet
    5. 4. THE aiNet FAMILY OF ALGORITHMS
    6. 5. ARTIFICIAL IMMUNE NETWORKS FOR OPTIMIZATION
    7. 6. ARTIFICIAL IMMUNE NETWORKS FOR BICLUSTERING
    8. 7. FINAL COMMENTS
  7. Chapter 2: Cognitively Inspired Neural Network for Recognition of Situations
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. NEURAL MODELING FIELDS (NMF)
    4. 3. NMF-DL FOR LEARNING SITUATIONS
    5. 4. SIMULATION RESULTS
    6. 5. COMPUTATIONAL COMPLEXITY
    7. 6. DISCUSSION AND CONCLUSIONS
  8. Chapter 3: Wave Propagation in Filamental Cellular Automata
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. SOME GENERAL POINTS
    4. 3. TYPE B WAVES AND CLOCK AUTOMATA
    5. 4. TYPE A WAVES WITH 2-STATE AND 3-STATE AUTOMATA
    6. 5. VIABLE POPULATIONS OF 3-STATE SYMMETRIC AUTOMATA
    7. 6. SUMMARY AND OPEN PROBLEMS
  9. Chapter 4: Quantum Automata with Open Time Evolution1
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. PRELIMINARIES ON FINITE AUTOMATA
    4. 3. FORMALISM OF QUANTUM MECHANICS
    5. 4. QUANTUM AUTOMATA WITH OPEN TIME EVOLUTION
    6. 5. SIMULATING OTHER TYPES OF AUTOMATA
    7. CONCLUSION
  10. Chapter 5: A Grasp with Path-Relinking for the Workover Rig Scheduling Problem
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. BRIEF LITERATURE REVIEW OF THE WRS PROBLEM
    4. 3. MATHEMATICAL FORMULATION FOR THE WRS PROBLEM
    5. 4. GRASP+PR
    6. 5. COMPUTATIONAL RESULTS
    7. 6. CONCLUSION
  11. Chapter 6: A New Differential Evolution Based Metaheuristic for Discrete Optimization
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. DIFFERENTIAL EVOLUTION FOR CONTINUOUS OPTIMIZATION
    4. 3. DIFFERENTIAL EVOLUTION FOR DISCRETE OPTIMIZATION
    5. 4. RESULTS
    6. 5. CONCLUSION
  12. Chapter 7: Memetic and Evolutionary Design of Wireless Sensor Networks Based on Complex Network Characteristics
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. PROBLEM DEFINITION
    4. 3. PROBLEM FORMULATION
    5. 4. SOLUTION BASED ON GENETIC ALGORITHMS
    6. 5. COMPUTATIONAL RESULTS
    7. 6. CONCLUSION AND FUTURE RESEARCH DIRECTIONS
  13. Chapter 8: An Improved Artificial Bee Colony Algorithm for the Object Recognition Problem in Complex Digital Images Using Template Matching
    1. ABSTRACT
    2. 1. INTRODUCTION AND RELATED WORK
    3. 2. DESCRIPTION OF THE OBJECT RECOGNITION PROBLEM
    4. 3. BEE COLONIES IN NATURE
    5. 4. BEES FORAGING BEHAVIOR
    6. 5. DETAILS OF THE ARTIFICIAL BEE COLONY ALGORITHM
    7. 6. THE ABC ALGORITHM FOR THE OBJECT RECOGNITION PROBLEM
    8. 7. THE IMPROVED ABC ALGORITHM FOR THE OBJECT RECOGNITION PROBLEM
    9. 8. COMPUTATIONAL EXPERIMENTS AND RESULTS
    10. 9. DISCUSSION OF RESULTS
    11. 10. CONCLUSION
  14. Chapter 9: Feature Selection for Bankruptcy Prediction
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. BANKRUPTCY PREDICTION
    4. 3. MULTI-OBJECTIVE OPTIMIZATION
    5. 4. RESULTS AND DISCUSSION
    6. 5. CONCLUSION
  15. Chapter 10: Robust Design of Power Distribution Systems Using an Enhanced Multi-Objective Genetic Algorithm
    1. ABSTRACT
    2. INTRODUCTION
    3. CONTINUOUS-SPACE CONCEPTS IN NETWORK PROBLEMS
    4. METHODOLOGY
    5. RESULTS AND DISCUSSION
    6. CONCLUSION
  16. Chapter 11: Simulation of Multiple Cell Population Dynamics Using a 3-D Cellular Automata Model for Tissue Growth
    1. ABSTRACT
    2. INTRODUCTION
    3. CELLULAR AUTOMATA CONCEPTS
    4. THE MODEL
    5. STATES OF THE CELLULAR AUTOMATON
    6. ALGORITHM
    7. SIMULATION RESULTS AND DISCUSSION
    8. CONCLUSION
  17. Chapter 12: Comparison of Zipper and Non-Zipper Merging Patterns Near Merging Point of Roads
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. VEHICLE FOLLOWING MODELS AND STABILITY CONDITIONS
    4. 3. CELLULAR AUTOMATA MODEL
    5. 4. NUMERICAL RESULTS
    6. 5. CONCLUSION
  18. Chapter 13: Adaptability and Homeostasis in the Game of Life interacting with the evolved Cellular Automata
    1. ABSTRACT
    2. INTRODUCTION
    3. THE MODEL
    4. THE TARGET BEHAVIOR OF THE MODEL
    5. GENETIC ALGORITHM
    6. RESULT
    7. DISCUSSION
  19. Chapter 14: Conspecific Emotional Cooperation Biases Population Dynamics
    1. ABSTRACT
    2. INTRODUCTION
    3. PREVIOUS WORK
    4. OUR MODEL
    5. RULES ENHANCED BY EMOTIONS
    6. RESULTS
    7. CONCLUSION
  20. Chapter 15: Cellular Automata Communication Models
    1. ABSTRACT
    2. 1. INTRODUCTION AND MOTIVATION
    3. 2 CELLULAR AUTOMATA BASICS
    4. 3. ON TEMPORAL CYCLES IN PARALLEL AND SEQUENTIAL SIMPLE THRESHOLD CELLULAR AUTOMATA
    5. 4. ON GENUINELY ASYNCHRONOUS CELLULAR AUTOMATA
    6. 5. SUMMARY
    7. REFERENCES
  21. Chapter 16: Response Curves for Cellular Automata in One and Two Dimensions
    1. ABSTRACT
    2. INTRODUCTION
    3. BASIC DEFINITIONS
    4. STRUCTURE OF PREIMAGE SETS IN ONE DIMENSION
    5. DEPENDENCE ON THE INITIAL DENSITY IN ONE DIMENSION
    6. BASIC DEFINITIONS IN TWO DIMENSIONS
    7. STRUCTURE OF PREIMAGE SETS IN TWO DIMENSIONS
    8. DEPENDENCE ON THE INITIAL DENSITY IN TWO DIMENSIONS
    9. CONCLUSION AND FUTURE WORK
  22. Chapter 17: Segmentation and Feature Extraction of Panoramic Dental X-Ray Images
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. DATABASE SAMPLES
    4. 3. PROPOSED METHOD
    5. 4. EXPERIMENTAL RESULTS
    6. 5. CONCLUSION AND FUTURE WORK
  23. Chapter 18: Analysis of a Step-Based Watershed Algorithm Using CUDA
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. WATERSHED TRANSFORM
    4. 3. GPU PROCESSING
    5. 4. ALGORITHM PROPOSAL
    6. 5. EXPERIMENTAL RESULTS
    7. 6. CONCLUSION
  24. Chapter 19: Object Tracking by Multiple State Management and Eigenbackground Segmentation
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. OBJECT MANAGEMENT
    4. 3. EXPERIMENTS RESULTS
    5. 4. CONCLUSION
  25. Chapter 20: Microscope Volume Segmentation Improved through Non-Linear Restoration
    1. ABSTRACT
    2. INTRODUCTION
    3. OPTICAL MICROSCOPE VOLUMES
    4. SEGMENTATION AND EVALUATION METHODS
    5. RESULTS AND DISCUSSION
    6. CONCLUSION
  26. Chapter 21: Recognition of Human Silhouette Based on Global Features
    1. ABSTRACT
    2. INTRODUCTION
    3. RELATED WORK ON GAIT RECOGNITION
    4. METHODOLOGY
    5. MATERIALS
    6. RESULTS EVALUATION METHOD
    7. CONCLUSION
  27. Chapter 22: Mapping with Monocular Vision in Two Dimensions
    1. ABSTRACT
    2. INTRODUCTION
    3. PROBLEM GEOMETRY
    4. OBSTACLE DETECTION
    5. EXPERIMENT WITH REAL IMAGES
    6. CONCLUSION
  28. Compilation of References
  29. About the Contributors