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An Introductory Course in Computational Intelligence

Michael Chabon

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Published in Deep Learning In Computational Mechanics: An Introductory Course (Studies In Computational Intelligence 977)

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Deep Learning in Computational Mechanics: An Introductory Course (Studies in Computational Intelligence 977)

Deep Learning in Computational Mechanics: An Introductory Course (Studies in Computational Intelligence Book 977)

by Sun Tzu

4.1 out of 5

Language	:	English
File size	:	17092 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Print length	:	252 pages

What is Computational Intelligence?

Computational intelligence (CI) is a field of artificial intelligence that deals with the design and development of intelligent systems. CI systems are typically designed to mimic the cognitive abilities of humans, such as learning, problem solving, and decision making.

CI has a wide range of applications, including:

* Robotics * Image processing * Natural language processing * Medical diagnosis * Financial forecasting

The Fundamental Concepts of Computational Intelligence

The fundamental concepts of CI include:

* **Fuzzy logic:** Fuzzy logic is a form of logic that deals with imprecise or uncertain information. Fuzzy logic systems are often used to model complex systems that are difficult to describe using traditional logic. * **Neural networks:** Neural networks are computational models that are inspired by the human brain. Neural networks can be used to learn from data and to solve a variety of problems, such as image recognition and natural language processing. * **Evolutionary computation:** Evolutionary computation is a computational method that is inspired by the process of natural selection. Evolutionary computation algorithms can be used to solve a variety of optimization problems, such as finding the shortest path between two points or the optimal design for a product.

Hands-on Examples and Exercises

This book provides a number of hands-on examples and exercises to help readers apply the concepts of CI to real-world problems. These examples and exercises cover a wide range of topics, including:

* How to use fuzzy logic to model a traffic light controller * How to use neural networks to recognize handwritten digits * How to use evolutionary computation to design a robot

This book provides a comprehensive to CI, a rapidly growing field with a wide range of applications. The book covers the fundamental concepts of CI, including fuzzy logic, neural networks, and evolutionary computation, and provides hands-on examples and exercises to help readers apply these concepts to real-world problems.

Deep Learning in Computational Mechanics: An Introductory Course (Studies in Computational Intelligence Book 977)

by Sun Tzu

4.1 out of 5