Skip to main content
View Cart

Bio-inspired Algorithms for Engineering

  • 1st Edition - January 30, 2018
  • Latest edition
  • Authors: Nancy Arana-Daniel, Carlos Lopez-Franco, Alma Y Alanis
  • Language: English

Bio-inspired Algorithms for Engineering builds a bridge between the proposed bio-inspired algorithms developed in the past few decades and their applications in real-life problems,… Read more

Early spring sale

Nurture your knowledge

Grow your expertise with up to 25% off trusted resources.

Shop now

Description

Bio-inspired Algorithms for Engineering builds a bridge between the proposed bio-inspired algorithms developed in the past few decades and their applications in real-life problems, not only in an academic context, but also in the real world. The book proposes novel algorithms to solve real-life, complex problems, combining well-known bio-inspired algorithms with new concepts, including both rigorous analyses and unique applications. It covers both theoretical and practical methodologies, allowing readers to learn more about the implementation of bio-inspired algorithms. This book is a useful resource for both academic and industrial engineers working on artificial intelligence, robotics, machine learning, vision, classification, pattern recognition, identification and control.

Key features

  • Presents real-time implementation and simulation results for all the proposed schemes
  • Offers a comparative analysis and rigorous analysis of the convergence of proposed algorithms
  • Provides a guide for implementing each application at the end of each chapter
  • Includes illustrations, tables and figures that facilitate the reader’s comprehension of the proposed schemes and applications

Readership

Research Engineers working on artificial intelligence, robotics, machine learning, vision, classification, pattern recognition, identification and control, among others. Professors and Graduate students working on artificial intelligence, robotics, machine learning, vision, classification, pattern recognition, identification and control

Table of contents

1. Bio-inspired Algorithms2. Data Classification Using Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron3. Reconstruction of 3D Surfaces Using RBF Adjusted with PSO4. Soft Computing Applications in Robot Vision5. Soft Computing Applications inMobile Robotics6. Particle Swarm Optimization to Improve Neural Identifiers for Discrete-time Unknown Nonlinear Systems7. Bio-inspired Algorithms to Improve Neural Controllers for Discrete-time Unknown Nonlinear System8. Final Remarks

Product details

  • Edition: 1
  • Latest edition
  • Published: February 3, 2018
  • Language: English

About the authors

NA

Nancy Arana-Daniel

Nancy Arana-Daniel received her B. Sc. Degree from the University of Guadalajara in 2000, and her M. Sc. And Ph.D. degrees in electric engineering with the special field in computer sicence from Research Center of the National Polytechnic Institute and Advanced Studies, CINVESTAV, in 2003 and 2007 respectively. She is currently a research fellow at the University of Guadalajara, in the Department of Computer Science Mxico, where she is working at the Laboratory of Intelligent Systems and the Research Center for Control Systems and Artificial Intelligence. She is IEEE Senior member and a member of National System of Researchers (SNI-1). She has published several papers in International Journals and Conferences and she has been technical manager of several projects that have been granted by the Nacional Council of Science and Technology (CONACYT). Also, se has collaborated in an international project granted by OPTREAT), She is Associated Editor of the Journal of Franklin Institute (Elsevier). Her research interests focus on applications of geometric algebra, geometric computing, machine learning, bio-inspired optimization, pattern recognition and robot navigation.
Affiliations and expertise
University of Guadalajara, Guadalajara, Jalisco, Mexico

CL

Carlos Lopez-Franco

Carlos Lpez-Franco received the Ph.D. degree in Computer Science in 2007 from the Center of Research and Advanced Studies, CINVESTAV, Mexico. He is currently a professor at the University of Guadalajara, Mexico, Computer Science Department, and member of the Intelligent Systems group. He is IEEE Senior member and a member of National System of Researchers) or SNI, level 1. His research interests include geometric algebra, computer vision, robotics and intelligent systems.
Affiliations and expertise
University of Guadalajara, Guadalajara, Jalisco, Mexico

AY

Alma Y Alanis

Alma Y. Alanis received a Ph.D. degree in electrical engineering from the Advanced Studies and Research Center of the National Polytechnic Institute (CINVESTAV-IPN), Guadalajara Campus, Mexico, in 2007. Since 2008, she has been with the University of Guadalajara, where she is currently a Chair Professor in the Department of Computer Science. She is also a member of the Mexican National Research System (SNI-3) and the Mexican Academy of Sciences. She has published papers in recognized international journals and conferences, as well as eight international books. She is a Senior Member of the IEEE and a Subject Editor for the Journal of Franklin Institute (Elsevier), IEEE/ASME Transactions on Mechatronics, IEEE Access, IEEE Latin American Transactions, and Intelligent Automation & Soft Computing. In 2013, she received the grant for women in science by L'Oreal-UNESCO-AMC-CONACYT-CONALMEX. In 2015, she received the Marcos Moshinsky Research Award. Since 2008, she has been a member of the Accredited Assessors record RCEA-CONACYT, evaluating a wide range of national research projects, and has served on important national and international project evaluation committees. Her research interests center on neural control, backstepping control, block control, and their applications to electrical machines, power systems, and robotics.

Affiliations and expertise
Dean of Technologies for Cyber-Human Interaction Division (CUCEI), Universidad de Guadalajara, Mexico

View book on ScienceDirect

Read Bio-inspired Algorithms for Engineering on ScienceDirect