Evolutionary Computation Techniques: A Comparative Perspective PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Evolutionary Computation Techniques: A Comparative Perspective PDF full book. Access full book title Evolutionary Computation Techniques: A Comparative Perspective by Erik Cuevas. Download full books in PDF and EPUB format.

Evolutionary Computation Techniques: A Comparative Perspective

Evolutionary Computation Techniques: A Comparative Perspective PDF Author: Erik Cuevas
Publisher: Springer
ISBN: 3319511092
Category : Technology & Engineering
Languages : en
Pages : 236

Book Description
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.

Evolutionary Computation Techniques: A Comparative Perspective

Evolutionary Computation Techniques: A Comparative Perspective PDF Author: Erik Cuevas
Publisher: Springer
ISBN: 3319511092
Category : Technology & Engineering
Languages : en
Pages : 236

Book Description
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.

Evolutionary Computation

Evolutionary Computation PDF Author: Ashish M. Gujarathi
Publisher: CRC Press
ISBN: 1771883375
Category : Computers
Languages : en
Pages : 652

Book Description
Edited by professionals with years of experience, this book provides an introduction to the theory of evolutionary algorithms and single- and multi-objective optimization, and then goes on to discuss to explore applications of evolutionary algorithms for many uses with real-world applications. Covering both the theory and applications of evolutionary computation, the book offers exhaustive coverage of several topics on nontraditional evolutionary techniques, details working principles of new and popular evolutionary algorithms, and discusses case studies on both scientific and real-world applications of optimization

Metaheuristics in Machine Learning: Theory and Applications

Metaheuristics in Machine Learning: Theory and Applications PDF Author: Diego Oliva
Publisher: Springer Nature
ISBN: 3030705420
Category : Computational intelligence
Languages : en
Pages : 765

Book Description
This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolutionary, swarm, machine learning, and deep learning. The chapters were classified based on the content; then, the sections are thematic. Different applications and implementations are included; in this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities.

New Advancements in Swarm Algorithms: Operators and Applications

New Advancements in Swarm Algorithms: Operators and Applications PDF Author: Erik Cuevas
Publisher: Springer
ISBN: 3030163393
Category : Technology & Engineering
Languages : en
Pages : 296

Book Description
This book presents advances in alternative swarm development that have proved to be effective in several complex problems. Swarm intelligence (SI) is a problem-solving methodology that results from the cooperation between a set of agents with similar characteristics. The study of biological entities, such as animals and insects, manifesting social behavior has resulted in several computational models of swarm intelligence. While there are numerous books addressing the most widely known swarm methods, namely ant colony algorithms and particle swarm optimization, those discussing new alternative approaches are rare. The focus on developments based on the simple modification of popular swarm methods overlooks the opportunity to discover new techniques and procedures that can be useful in solving problems formulated by the academic and industrial communities. Presenting various novel swarm methods and their practical applications, the book helps researchers, lecturers, engineers and practitioners solve their own optimization problems.

Applications of Flower Pollination Algorithm and its Variants

Applications of Flower Pollination Algorithm and its Variants PDF Author: Nilanjan Dey
Publisher: Springer Nature
ISBN: 9813361042
Category : Technology & Engineering
Languages : en
Pages : 239

Book Description
This book presents essential concepts of traditional Flower Pollination Algorithm (FPA) and its recent variants and also its application to find optimal solution for a variety of real-world engineering and medical problems. Swarm intelligence-based meta-heuristic algorithms are extensively implemented to solve a variety of real-world optimization problems due to its adaptability and robustness. FPA is one of the most successful swarm intelligence procedures developed in 2012 and extensively used in various optimization tasks for more than a decade. The mathematical model of FPA is quite straightforward and easy to understand and enhance, compared to other swarm approaches. Hence, FPA has attracted attention of researchers, who are working to find the optimal solutions in variety of domains, such as N-dimensional numerical optimization, constrained/unconstrained optimization, and linear/nonlinear optimization problems. Along with the traditional bat algorithm, the enhanced versions of FPA are also considered to solve a variety of optimization problems in science, engineering, and medical applications.

Applications of Hybrid Metaheuristic Algorithms for Image Processing

Applications of Hybrid Metaheuristic Algorithms for Image Processing PDF Author: Diego Oliva
Publisher: Springer Nature
ISBN: 3030409775
Category : Technology & Engineering
Languages : en
Pages : 488

Book Description
This book presents a collection of the most recent hybrid methods for image processing. The algorithms included consider evolutionary, swarm, machine learning and deep learning. The respective chapters explore different areas of image processing, from image segmentation to the recognition of objects using complex approaches and medical applications. The book also discusses the theory of the methodologies used to provide an overview of the applications of these tools in image processing. The book is primarily intended for undergraduate and postgraduate students of science, engineering and computational mathematics, and can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence. Further, it is a valuable resource for researchers from the evolutionary computation, artificial intelligence and image processing communities.

Analysis and Comparison of Metaheuristics

Analysis and Comparison of Metaheuristics PDF Author: Erik Cuevas
Publisher: Springer Nature
ISBN: 3031201051
Category : Technology & Engineering
Languages : en
Pages : 230

Book Description
This book presents a comparative perspective of current metaheuristic developments, which have proved to be effective in their application to several complex problems. The study of biological and social entities such as animals, humans, or insects that manifest a cooperative behavior has produced several computational models in metaheuristic methods. Although these schemes emulate very different processes or systems, the rules used to model individual behavior are very similar. Under such conditions, it is not clear to identify which are the advantages or disadvantages of each metaheuristic technique. The book is compiled from a teaching perspective. For this reason, the book is primarily intended for undergraduate and postgraduate students of Science, Electrical Engineering, or Computational Mathematics. It is appropriate for courses such as Artificial Intelligence, Electrical Engineering, Evolutionary Computation. The book is also useful for researchers from the evolutionary and engineering communities. Likewise, engineer practitioners, who are not familiar with metaheuristic computation concepts, will appreciate that the techniques discussed are beyond simple theoretical tools since they have been adapted to solve significant problems that commonly arise in engineering areas.

Evolutionary Computation with Intelligent Systems

Evolutionary Computation with Intelligent Systems PDF Author: R.S. Chauhan
Publisher: CRC Press
ISBN: 1000550540
Category : Technology & Engineering
Languages : en
Pages : 316

Book Description
This book focuses on cutting-edge innovations and core theories, principles, and algorithms applicable to a wide area. Real-life applications, case studies, and examples are included along with emerging trends, design, and optimized solutions pivoting around the needs of Society 5.0. Evolutionary Computation with Intelligent Systems: A Multidisciplinary Approach to Society 5.0 provides a holistic view of evolutionary computation techniques including principles, procedures, and future applications with real-life examples. The book comprehensively explains evolutionary computation, design, principles, development trends, and optimization and describes how it can transform the operating context of the organization. It exemplifies the potential of evolutionary computation for the next generation and the role of cloud computing in shaping Society 5.0. It also provides insight into various platforms, paradigms, techniques, and tools used in diverse fields. This book appeals to a variety of readers such as academicians, researchers, research scholars, and postgraduates.

Advances in Evolutionary Computing

Advances in Evolutionary Computing PDF Author: Ashish Ghosh
Publisher: Springer Science & Business Media
ISBN: 3642189652
Category : Computers
Languages : en
Pages : 1001

Book Description
This book provides a collection of fourty articles containing new material on both theoretical aspects of Evolutionary Computing (EC), and demonstrating the usefulness/success of it for various kinds of large-scale real world problems. Around 23 articles deal with various theoretical aspects of EC and 17 articles demonstrate the success of EC methodologies. These articles are written by leading experts of the field from different countries all over the world.

Experimental Research in Evolutionary Computation

Experimental Research in Evolutionary Computation PDF Author: Thomas Bartz-Beielstein
Publisher: Springer Science & Business Media
ISBN: 354032027X
Category : Computers
Languages : en
Pages : 221

Book Description
This book introduces the new experimentalism in evolutionary computation, providing tools to understand algorithms and programs and their interaction with optimization problems. It develops and applies statistical techniques to analyze and compare modern search heuristics such as evolutionary algorithms and particle swarm optimization. The book bridges the gap between theory and experiment by providing a self-contained experimental methodology and many examples.