Type-3 Fuzzy Logic in Time Series Prediction / by Oscar Castillo, Patricia Melin.

Format:

Book

Author/Creator:

Castillo, Oscar.

Contributor:

Melin, Patricia.

Series:

SpringerBriefs in Computational Intelligence, 2625-3712

Language:

English

Subjects (All):

Computational intelligence.

Engineering mathematics.

Computational Intelligence.

Engineering Mathematics.

Local Subjects:

Computational Intelligence.

Engineering Mathematics.

Physical Description:

1 online resource (102 pages)

Edition:

1st ed. 2024.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2024.

Summary:

This book focuses on the field of type-3 fuzzy logic for applications in time series prediction. The main idea is that a higher type and order of fuzzy logic can help in solving various prediction problems and find better results. In addition, neural networks and fractal theory are employed in enhancing prediction results. In this regard, several hybrid intelligent methods are offered. In this book we test the proposed methods using several prediction problems, like predicting COVID-19 and the stock market. We can notice that when Type-3 fuzzy systems are implemented to model the behavior of systems, the results in prediction are enhanced, because the management of uncertainty is better. For this reason, we consider in this book the proposed methods using type-3 fuzzy systems, neural networks and fractal theory to improve the prediction behavior of the complex nonlinear systems. This book is intended to be a reference for scientists and engineers interested in applying type-3 fuzzy logic techniques for solving complex prediction problems. This book can also be used as a reference for graduate courses like the following: soft computing, fuzzy logic, neural networks, bio-inspired algorithms, intelligent prediction, and similar ones. We consider that this book can also be used to get novel ideas for new lines of research, or to continue the lines of research proposed by the authors of the book.

Contents:

Chapter1. Type-3 Fuzzy Prediction

Chapter 2. Type-3 for Prediction

Chapter 3. Type-3 Fuzzy Logic in Time Series Prediction

Chapter 4. Prediction with a Hybrid Interval Type-3 Fuzzy-Fractal Approach

Chapter 5. Type-3 Fuzzy Aggregation of Neural Networks.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

9783031597145

3031597141

OCLC:

1434176679