Книга Artificial Intelligence for Cognitive Modeling: Theory and Practice

Формат
Язык книги
Издательство
Год издания

This book is written in a clear and thorough way to cover both the traditional and modern uses of artificial intelligence and soft computing. It gives an in-depth look at mathematical models, algorithms, and real-world problems that are hard to solve in MATLAB. The book is intended to provide a broad and in-depth understanding of fuzzy logic controllers, genetic algorithms, neural networks, and hybrid techniques such as ANFIS and the GA-ANN model.

Features:

  • A detailed description of basic intelligent techniques (fuzzy logic, genetic algorithm and neural network using MATLAB)
  • A detailed description of the hybrid intelligent technique called the adaptive fuzzy inference technique (ANFIS)
  • Formulation of the nonlinear model like analysis of ANOVA and response surface methodology
  • Variety of solved problems on ANOVA and RSM
  • Case studies of above mentioned intelligent techniques on the different process control systems

This book can be used as a handbook and a guide for students of all engineering disciplines, operational research areas, computer applications, and for various professionals who work in the optimization area.

Код товара
20421007
Характеристики
Тип обложки
Твердый
Язык
Английский
Доставка и оплата
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Описание книги

This book is written in a clear and thorough way to cover both the traditional and modern uses of artificial intelligence and soft computing. It gives an in-depth look at mathematical models, algorithms, and real-world problems that are hard to solve in MATLAB. The book is intended to provide a broad and in-depth understanding of fuzzy logic controllers, genetic algorithms, neural networks, and hybrid techniques such as ANFIS and the GA-ANN model.

Features:

  • A detailed description of basic intelligent techniques (fuzzy logic, genetic algorithm and neural network using MATLAB)
  • A detailed description of the hybrid intelligent technique called the adaptive fuzzy inference technique (ANFIS)
  • Formulation of the nonlinear model like analysis of ANOVA and response surface methodology
  • Variety of solved problems on ANOVA and RSM
  • Case studies of above mentioned intelligent techniques on the different process control systems

This book can be used as a handbook and a guide for students of all engineering disciplines, operational research areas, computer applications, and for various professionals who work in the optimization area.

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