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Bio-inspired algorithms for engineering /
"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-lif...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Oxford, United Kingdom :
Butterworth-Heinemann, an imprint of Elsevier,
[2018]
|
| Edición: | First edition. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
| LEADER | 00000cam a2200000 i 4500 | ||
|---|---|---|---|
| 001 | SCIDIR_on1021172444 | ||
| 003 | OCoLC | ||
| 005 | 20231120010243.0 | ||
| 006 | m o d | ||
| 007 | cr cnu|||unuuu | ||
| 008 | 180201s2018 enk ob 001 0 eng d | ||
| 040 | |a N$T |b eng |e rda |e pn |c N$T |d EBLCP |d NLE |d N$T |d OPELS |d STF |d YDX |d D6H |d OCLCF |d INT |d OCLCQ |d U3W |d LVT |d OCLCQ |d UMI |d G3B |d UPM |d C6I |d OCLCQ |d OCLCO |d K6U |d OCLCQ |d SFB |d OCLCQ |d OCLCO | ||
| 019 | |a 1021291470 |a 1082522817 | ||
| 020 | |a 9780128137895 |q (electronic bk.) | ||
| 020 | |a 0128137894 |q (electronic bk.) | ||
| 020 | |z 9780128137888 | ||
| 020 | |z 0128137886 | ||
| 035 | |a (OCoLC)1021172444 |z (OCoLC)1021291470 |z (OCoLC)1082522817 | ||
| 050 | 4 | |a QA76.9.A43 | |
| 072 | 7 | |a COM |x 051300 |2 bisacsh | |
| 082 | 0 | 4 | |a 005.1 |2 23 |
| 100 | 1 | |a Alanis, Alma Y., |e author. | |
| 245 | 1 | 0 | |a Bio-inspired algorithms for engineering / |c Alma Y. Alanis, Nancy Arana-Daniel, Carlos L�opez-Franco. |
| 250 | |a First edition. | ||
| 264 | 1 | |a Oxford, United Kingdom : |b Butterworth-Heinemann, an imprint of Elsevier, |c [2018] | |
| 264 | 4 | |c �2018 | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 588 | |a Online resource; title from PDF title page (EBSCO, viewed February 13, 2018). | ||
| 504 | |a Includes bibliographical references and index. | ||
| 520 | |a "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. 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 chapterIncludes illustrations, tables and figures that facilitate the reader's comprehension of the proposed schemes and applications"-- |c Provided by publisher | ||
| 505 | 0 | |a Intro; Title page; Table of Contents; Copyright; Dedication; Preface; Acknowledgments; Chapter One: Bio-inspired Algorithms; Abstract; 1.1. Introduction; 1.2. Particle Swarm Optimization; 1.3. Artificial Bee Colony Algorithm; 1.4. Micro Artificial Bee Colony Algorithm; 1.5. Differential Evolution; 1.6. Bacterial Foraging Optimization Algorithm; References; Chapter Two: Data Classification Using Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron; Abstract; 2.1. Introduction; 2.2. Support Vector Machines; 2.3. Evolutionary algorithms. | |
| 505 | 8 | |a 2.4. The Kernel Adatron algorithm2.5. Kernel Adatron trained with evolutionary algorithms; 2.6. Results using benchmark repository datasets; 2.7. Application to classify electromyographic signals; 2.8. Conclusions; References; Chapter Three: Reconstruction of 3D Surfaces Using RBF Adjusted with PSO; Abstract; 3.1. Introduction; 3.2. Radial basis functions; 3.3. Interpolation of surfaces with RBF and PSO; 3.4. Conclusion; References; Chapter Four: Soft Computing Applications in Robot Vision; Abstract; 4.1. Introduction; 4.2. Image tracking; 4.3. Plane detection; 4.4. Conclusion; References. | |
| 505 | 8 | |a Chapter Five: Soft Computing Applications in Mobile RoboticsAbstract; 5.1. Introduction to mobile robotics; 5.2. Nonholonomic mobile robot navigation; 5.3. Holonomic mobile robot navigation; 5.4. Conclusion; References; Chapter Six: Particle Swarm Optimization to Improve Neural Identifiers for Discrete-time Unknown Nonlinear Systems; Abstract; 6.1. Introduction; 6.2. Particle-swarm-based approach of a real-time discrete neural identifier for Linear Induction Motors; 6.3. Neural model with particle swarm optimization Kalman learning for forecasting in smart grids; 6.4. Conclusions; References. | |
| 505 | 8 | |a Chapter Seven: Bio-inspired Algorithms to Improve Neural Controllers for Discrete-time Unknown Nonlinear SystemAbstract; 7.1. Neural Second-Order Sliding Mode Controller for unknown discrete-time nonlinear systems; 7.2. Neural-PSO Second-Order Sliding Mode Controller for unknown discrete-time nonlinear systems; 7.3. Neural-BFO Second-Order Sliding Mode Controller for unknown discrete-time nonlinear systems; 7.4. Comparative analysis; 7.5. Conclusions; References; Chapter Eight: Final Remarks; Index. | |
| 650 | 0 | |a Computer algorithms. | |
| 650 | 0 | |a Natural computation |x Industrial applications. | |
| 650 | 0 | |a Evolutionary computation |x Industrial applications. | |
| 650 | 0 | |a Natural computation |x Scientific applications. | |
| 650 | 0 | |a Evolutionary computation |x Scientific applications. | |
| 650 | 2 | |a Algorithms |0 (DNLM)D000465 | |
| 650 | 6 | |a Algorithmes. |0 (CaQQLa)201-0001230 | |
| 650 | 6 | |a Calcul naturel |0 (CaQQLa)000265307 |x Applications industrielles. |0 (CaQQLa)201-0374039 | |
| 650 | 6 | |a R�eseaux neuronaux �a structure �evolutive |0 (CaQQLa)201-0299688 |x Applications industrielles. |0 (CaQQLa)201-0374039 | |
| 650 | 6 | |a Calcul naturel |0 (CaQQLa)000265307 |x Applications scientifiques. |0 (CaQQLa)201-0373912 | |
| 650 | 6 | |a R�eseaux neuronaux �a structure �evolutive |0 (CaQQLa)201-0299688 |x Applications scientifiques. |0 (CaQQLa)201-0373912 | |
| 650 | 7 | |a algorithms. |2 aat |0 (CStmoGRI)aat300065585 | |
| 650 | 7 | |a COMPUTERS |x Programming |x Algorithms. |2 bisacsh | |
| 650 | 7 | |a Computer algorithms |2 fast |0 (OCoLC)fst00872010 | |
| 700 | 1 | |a Arana-Daniel, Nancy, |e author. | |
| 700 | 1 | |a Lopez-Franco, Carlos, |e author. | |
| 776 | 0 | 8 | |i Print version: |a Alanis, Alma Y. |t Bio-inspired algorithms for engineering. |b First edition. |d Oxford, United Kingdom : Butterworth-Heinemann, an imprint of Elsevier, [2018] |z 0128137886 |z 9780128137888 |w (OCoLC)994463742 |
| 856 | 4 | 0 | |u https://sciencedirect.uam.elogim.com/science/book/9780128137888 |z Texto completo |