Proceedings of the ... IEEE Conference on Evolutionary Computation
Author:
Publisher:
Published: 1998
Total Pages: 878
ISBN-13:
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Proceedings of the First IEEE Conference on Evolutionary Computation
Author:
Publisher: IEEE Computer Society Press
Published: 1994
Total Pages: 568
ISBN-13:
DOWNLOAD EBOOKGenetic and Evolutionary Computing
Author: Jeng-Shyang Pan
Publisher: Springer Nature
Published: 2020-03-12
Total Pages: 587
ISBN-13: 9811533083
DOWNLOAD EBOOKThis book gathers papers presented at the 13th International Conference on Genetic and Evolutionary Computing (ICGEC 2019), which was held in Qingdao, China, from 1st to 3rd, November 2019. Since it was established, in 2006, the ICGEC conference series has been devoted to new approaches with a focus on evolutionary computing. Today, it is a forum for the researchers and professionals in all areas of computational intelligence including evolutionary computing, machine learning, soft computing, data mining, multimedia and signal processing, swarm intelligence and security. The book appeals to policymakers, academics, educators, researchers in pedagogy and learning theory, school teachers, and other professionals in the learning industry, and further and continuing education.
1998 IEEE International Conference on Evolutionary Computation Proceedings
Author: IEEE Neural Networks Council
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
Published: 1998
Total Pages: 872
ISBN-13:
DOWNLOAD EBOOKThis collection of papers from the ICEC conference covers a wide range of aspects of evolutionary computing. This includes principles of evolutionary computation such as adaptation and self-adaption, variation operators, representational issues, and theoretical investigations.
Evolutionary Multi-Criterion Optimization
Author: Shigeru Obayashi
Publisher: Springer Science & Business Media
Published: 2007-02-12
Total Pages: 972
ISBN-13: 3540709274
DOWNLOAD EBOOKThis book constitutes the refereed proceedings of the 4th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2007, held in Matsushima, Japan in March 2007. The 65 revised full papers presented together with 4 invited papers are organized in topical sections on algorithm design, algorithm improvements, alternative methods, applications, engineering design, many objectives, objective handling, and performance assessments.
Information Computing And Automation (In 3 Volumes) - Proceedings Of The International Conference
Author: Jian Ping Li
Publisher: World Scientific
Published: 2008-04-25
Total Pages: 1645
ISBN-13: 9814471380
DOWNLOAD EBOOKWavelet analysis and its applications have become one of the fastest growing research areas in the past several years. Wavelet theory has been employed in many fields and applications, such as signal and image processing, communication systems, biomedical imaging, radar, air acoustics, and endless other areas. Active media technology is concerned with the development of autonomous computational or physical entities capable of perceiving, reasoning, adapting, learning, cooperating, and delegating in a dynamic environment.This book consists of carefully selected and received papers presented at the conference, and is an attempt to capture the essence of the current state-of-the-art in wavelet analysis and active media technology. Invited papers included in this proceedings includes contributions from Prof P Zhang, T D Bui, and C Y Suen from Concordia University, Canada; Prof N A Strelkov and V L Dol'nikov from Yaroslavl State University, Russia; Prof Chin-Chen Chang and Ching-Yun Chang from Taiwan; Prof S S Pandey from R D University, India; and Prof I L Bloshanskii from Moscow State Regional University, Russia.
Proceedings of The Eighth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), 2013
Author: Zhixiang Yin
Publisher: Springer Science & Business Media
Published: 2013-10-22
Total Pages: 1209
ISBN-13: 3642375022
DOWNLOAD EBOOKInternational Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA) is one of the flagship conferences on Bio-Computing, bringing together the world’s leading scientists from different areas of Natural Computing. Since 2006, the conferences have taken place at Wuhan (2006), Zhengzhou (2007), Adelaide (2008), Beijing (2009), Liverpool & Changsha (2010), Malaysia (2011) and India (2012). Following the successes of previous events, the 8th conference is organized and hosted by Anhui University of Science and Technology in China. This conference aims to provide a high-level international forum that researchers with different backgrounds and who are working in the related areas can use to present their latest results and exchange ideas. Additionally, the growing trend in Emergent Systems has resulted in the inclusion of two other closely related fields in the BIC-TA 2013 event, namely Complex Systems and Computational Neuroscience. These proceedings are intended for researchers in the fields of Membrane Computing, Evolutionary Computing and Genetic Algorithms, DNA and Molecular Computing, Biological Computing, Swarm Intelligence, Autonomy-Oriented Computing, Cellular and Molecular Automata, Complex Systems, etc. Professor Zhixiang Yin is the Dean of the School of Science, Anhui University of Science & Technology, China. Professor Linqiang Pan is the head of the research group of Natural Computing at Huazhong University of Science and Technology, Wuhan, China. Professor Xianwen Fang also works at the Anhui University of Science & Technology.
Modeling Applications and Theoretical Innovations in Interdisciplinary Evolutionary Computation
Author: Samuelson Hong, Wei-Chiang
Publisher: IGI Global
Published: 2013-03-31
Total Pages: 357
ISBN-13: 1466636297
DOWNLOAD EBOOKEvolutionary computation has emerged as a major topic in the scientific community as many of its techniques have successfully been applied to solve problems in a wide variety of fields. Modeling Applications and Theoretical Innovations in Interdisciplinary Evolutionary Computation provides comprehensive research on emerging theories and its aspects on intelligent computation. Particularly focusing on breaking trends in evolutionary computing, algorithms, and programming, this publication serves to support professionals, government employees, policy and decision makers, as well as students in this scientific field.
Soft Computing for Image and Multimedia Data Processing
Author: Siddhartha Bhattacharyya
Publisher: Springer Science & Business Media
Published: 2013-10-04
Total Pages: 278
ISBN-13: 3642402550
DOWNLOAD EBOOKProper analysis of image and multimedia data requires efficient extraction and segmentation techniques. Among the many computational intelligence approaches, the soft computing paradigm is best equipped with several tools and techniques that incorporate intelligent concepts and principles. This book is dedicated to object extraction, image segmentation, and edge detection using soft computing techniques with extensive real-life application to image and multimedia data. The authors start with a comprehensive tutorial on the basics of brain structure and learning, and then the key soft computing techniques, including evolutionary computation, neural networks, fuzzy sets and fuzzy logic, and rough sets. They then present seven chapters that detail the application of representative techniques to complex image processing tasks such as image recognition, lighting control, target tracking, object extraction, and edge detection. These chapters follow a structured approach with detailed explanations of the problems, solutions, results, and conclusions. This is both a standalone textbook for graduates in computer science, electrical engineering, system science, and information technology, and a reference for researchers and engineers engaged with pattern recognition, image processing, and soft computing.
Extending the Scalability of Linkage Learning Genetic Algorithms
Author: Ying-ping Chen
Publisher: Springer Science & Business Media
Published: 2006
Total Pages: 152
ISBN-13: 9783540284598
DOWNLOAD EBOOKGenetic algorithms (GAs) are powerful search techniques based on principles of evolution and widely applied to solve problems in many disciplines. However, most GAs employed in practice nowadays are unable to learn genetic linkage and suffer from the linkage problem. The linkage learning genetic algorithm (LLGA) was proposed to tackle the linkage problem with several specially designed mechanisms. While the LLGA performs much better on badly scaled problems than simple GAs, it does not work well on uniformly scaled problems as other competent GAs. Therefore, we need to understand why it is so and need to know how to design a better LLGA or whether there are certain limits of such a linkage learning process. This book aims to gain better understanding of the LLGA in theory and to improve the LLGA's performance in practice. It starts with a survey of the existing genetic linkage learning techniques and describes the steps and approaches taken to tackle the research topics, including using promoters, developing the convergence time model, and adopting subchromosomes.
