Evolutionary Computation Techniques: A Comparative Perspective

✍ Scribed by Erik Cuevas, Valentín Osuna, Diego Oliva (auth.)

• Publisher: Springer International Publishing
• Year: 2017
• Tongue: English
• Leaves: 236
• Series: Studies in Computational Intelligence 686
• Edition: 1
• Category: Library

✦ Synopsis

This book compares the performance of various evolutionary computation (EC) techniques when they are faced with complex optimization problems extracted from different engineering domains. Particularly focusing on recently developed algorithms, it is designed so that each chapter can be read independently. Several comparisons among EC techniques have been reported in the literature, however, they all suffer from one limitation: their conclusions are based on the performance of popular evolutionary approaches over a set of synthetic functions with exact solutions and well-known behaviors, without considering the application context or including recent developments. In each chapter, a complex engineering optimization problem is posed, and then a particular EC technique is presented as the best choice, according to its search characteristics. Lastly, a set of experiments is conducted in order to compare its performance to other popular EC methods.

✦ Table of Contents

Front Matter....Pages i-xv
Introduction....Pages 1-8
Multilevel Segmentation in Digital Images....Pages 9-33
Multi-circle Detection on Images....Pages 35-64
Template Matching....Pages 65-93
Motion Estimation....Pages 95-116
Photovoltaic Cell Design....Pages 117-138
Parameter Identification of Induction Motors....Pages 139-154
White Blood Cells Detection in Images....Pages 155-180
Estimation of View Transformations in Images....Pages 181-204
Filter Design....Pages 205-222

✦ Subjects

Computational Intelligence;Artificial Intelligence (incl. Robotics)