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Women in Computational Intelligence

Key Advances and Perspectives on Emerging Topics

Medium: Buch
ISBN: 978-3-030-79091-2
Verlag: Springer International Publishing
Erscheinungstermin: 14.04.2022
Lieferfrist: bis zu 10 Tage

This book provides a breadth of innovative and impactful research in the field computational intelligence led by women investigators. Topics include intelligent data analytics, optimization of complex systems, approximation of human reasoning, robotic path planning, and intelligent control systems. These topics touch on many of the technological challenges facing the world today and these solutions by women researcher teams are valuable for their excellence and their non-traditional perspective. As an important part of the Women in Science and Engineering book series, the work highlights the contribution of women leaders in computational intelligence, inspiring women and men, girls, and boys to enter and apply themselves to this exciting multi-disciplinary field.


Produkteigenschaften


  • Artikelnummer: 9783030790912
  • Medium: Buch
  • ISBN: 978-3-030-79091-2
  • Verlag: Springer International Publishing
  • Erscheinungstermin: 14.04.2022
  • Sprache(n): Englisch
  • Auflage: 1. Auflage 2022
  • Serie: Women in Engineering and Science
  • Produktform: Gebunden
  • Gewicht: 846 g
  • Seiten: 445
  • Format (B x H x T): 160 x 241 x 30 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Herausgeber

Chapter 1. Amazing Grace – Computer Pioneer Admiral Grace Murray Hopper.- Chapter 2. XAI: A Natural Application Domain for Fuzzy Set Theory .- Chapter 3. Adaptive Physiological Profiling from Non-verbal Behaviour – Why Ethics are Just Not Enough to Build Trust.- Chapter 4. Conversational Intelligent Tutoring Systems - The State of the Art.- Chapter 5. Design and Validation of a Mini-game for Player Motive Profiling.- Chapter 6. When AI Meets Digital Pathology.- Chapter 7. Linguistic Intelligence as a Root for Computing Reasoning.- Chapter 8. Intrusion Detection: Deep Neural Networks versus Super Learning.- Chapter 9. Life-Long Learning Machines: Towards Developing Optimisation Methods That Continually Learn.- Chapter 10. Reinforcement Learning Control by Direct Heuristic Dynamic Programming.- Chapter 11. Distributed Machine Learning for Energy Management and Control in Smart Grid.- Chapter 12. Fuzzy Multilayer Perceptrons for Fuzzy Vector Regression.- Chapter 13. Generalisation in Genetic Programming for Symbolic Regression: Challenges and Future Directions.- Chapter 14. Neuro-evolutionary Models based on Quantum-Inspired Evolutionary Algorithms.- Chapter 15. Weightless Neural Models: An Overview.- Chapter 16. Challenges of Applying Dynamic Multi-objective Optimization to Real-world Problems.- Chapter 17. Computational Intelligence Methodologies for Multi-Objective Optimization and Decision-Making in Autonomous Systems.- Chapter 18. A Framework-Based Approach for Flexible Evaluation of Swarm-Intelligent Algorithms.- Chapter 19. An Improved Bat Algorithm with a Dimension-based Best for Numerical Optimization.