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Hybrid Computational Intelligence

- Challenges and Applications

About Hybrid Computational Intelligence

Hybrid Computational Intelligence: Challenges and Utilities is a comprehensive resource that begins with the basics and main components of computational intelligence. It brings together many different aspects of the current research on HCI technologies, such as neural networks, support vector machines, fuzzy logic and evolutionary computation, while also covering a wide range of applications and implementation issues, from pattern recognition and system modeling, to intelligent control problems and biomedical applications. The book also explores the most widely used applications of hybrid computation as well as the history of their development. Each individual methodology provides hybrid systems with complementary reasoning and searching methods which allow the use of domain knowledge and empirical data to solve complex problems. Provides insights into the latest research trends in hybrid intelligent algorithms and architecturesFocuses on the application of hybrid intelligent techniques for pattern mining and recognition, in big data analytics, and in human-computer interactionFeatures hybrid intelligent applications in biomedical engineering and healthcare informatics

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  • Language:
  • English
  • ISBN:
  • 9780128186992
  • Binding:
  • Paperback
  • Pages:
  • 250
  • Published:
  • March 5, 2020
  • Dimensions:
  • 152x229x0 mm.
  • Weight:
  • 410 g.
Delivery: 1-2 weeks
Expected delivery: November 29, 2024

Description of Hybrid Computational Intelligence

Hybrid Computational Intelligence: Challenges and Utilities is a comprehensive resource that begins with the basics and main components of computational intelligence. It brings together many different aspects of the current research on HCI technologies, such as neural networks, support vector machines, fuzzy logic and evolutionary computation, while also covering a wide range of applications and implementation issues, from pattern recognition and system modeling, to intelligent control problems and biomedical applications. The book also explores the most widely used applications of hybrid computation as well as the history of their development.
Each individual methodology provides hybrid systems with complementary reasoning and searching methods which allow the use of domain knowledge and empirical data to solve complex problems.

Provides insights into the latest research trends in hybrid intelligent algorithms and architecturesFocuses on the application of hybrid intelligent techniques for pattern mining and recognition, in big data analytics, and in human-computer interactionFeatures hybrid intelligent applications in biomedical engineering and healthcare informatics

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