Cargando…
New developments in evolutionary computation research /
A common approach for solving simulation-driven engineering problems is by using metamodel-assisted optimization algorithms, namely, in which a metamodel approximates the computationally expensive simulation and provides predicted values at a lower computational cost. Such algorithms typically gener...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hauppauge, New York :
Nova Science Publisher's Inc.,
[2014]
|
| Colección: | Computer science, technology and applications.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
| LEADER | 00000cam a2200000 i 4500 | ||
|---|---|---|---|
| 001 | EBSCO_ocn902846711 | ||
| 003 | OCoLC | ||
| 005 | 20231017213018.0 | ||
| 006 | m o d | ||
| 007 | cr cnu---unuuu | ||
| 008 | 150206s2014 nyu o 001 0 eng d | ||
| 040 | |a N$T |b eng |e rda |e pn |c N$T |d OCLCF |d YDXCP |d EBLCP |d DEBSZ |d OCLCA |d AGLDB |d OCLCQ |d JBG |d VTS |d STF |d M8D |d OCLCQ |d OCLCO |d OCLCQ |d OCLCO | ||
| 019 | |a 913695109 |a 923677876 |a 928197408 | ||
| 020 | |a 9781634635257 |q (electronic bk.) | ||
| 020 | |a 1634635256 |q (electronic bk.) | ||
| 020 | |z 9781634634939 | ||
| 020 | |z 1634634934 | ||
| 029 | 1 | |a DEBBG |b BV043031076 | |
| 029 | 1 | |a DEBSZ |b 42994036X | |
| 029 | 1 | |a DEBSZ |b 442851162 | |
| 035 | |a (OCoLC)902846711 |z (OCoLC)913695109 |z (OCoLC)923677876 |z (OCoLC)928197408 | ||
| 050 | 4 | |a TA347.E96 |b N49 2014eb | |
| 072 | 7 | |a COM |x 000000 |2 bisacsh | |
| 082 | 0 | 4 | |a 006.3/823 |2 23 |
| 049 | |a UAMI | ||
| 245 | 0 | 0 | |a New developments in evolutionary computation research / |c editor, Sean Washington. |
| 264 | 1 | |a Hauppauge, New York : |b Nova Science Publisher's Inc., |c [2014] | |
| 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 | ||
| 490 | 1 | |a Computer Science, Technology and Applications | |
| 500 | |a Includes index. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a NEW DEVELOPMENTS IN EVOLUTIONARY COMPUTATION RESEARCH; NEW DEVELOPMENTS IN EVOLUTIONARY COMPUTATION RESEARCH; LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA; CONTENTS; PREFACE; Chapter 1: MULTI-OBJECTIVE OPTIMIZATIONOF TRADING STRATEGIES USING GENETICALGORITHMS IN UNSTABLE ENVIRONMENTS; Abstract; A. Part A. Review of the Main Problem Solving and Optimization Techniques; B. Part B.A Review of Main Multi-Objective Optimization Techniques; C. Part C.A Case Study; Conclusion; References. | |
| 505 | 8 | |a Chapter 2: PROMOTING BETTER GENERALISATION IN MULTI-LAYER PERCEPTRONS USING A SIMULATED SYNAPTIC DOWNSCALING MECHANISMAbstract; 1. Introduction; 2. Background; 3. Model and Experiments; 4. Results and Analysis; 5. Conclusion; Acknowledgment; References; Chapter 3: PLANT PROPAGATION-INSPIRED ALGORITHMS; Abstract; 1. Introduction; 2. Background; 3. Plant Propagation Algorithms; 4. Applications; 5. Conclusion; References; Chapter 4: TOPOGRAPHICAL CLEARING DIFFERENTIAL EVOLUTION APPLIED TO REAL-WORLD MULTIMODAL OPTIMIZATION PROBLEMS; Abstract; 1. Introduction. | |
| 505 | 8 | |a 2. The Differential Evolution Algorithm3. Topographical Clearing; 4. Numerical Comparisons; 5. Conclusion; Appendix A. Nonlinear Systems Formulated as Optimization Problems; Appendix B. Data and Fitted Variables for the Catalytic Reactor Model; References; Chapter 5: ROBOTICS, EVOLUTION AND INTERACTIVITY IN SONIC ART INSTALLATIONS; Abstract; Introduction; 1. JaVOX, an Evolutionary Composition System; 2. Generative Sonification; 3. Automation x Interactivity; 4. Interactivity, Evolution and Structure; Conclusion; Acknowledgments; References. | |
| 505 | 8 | |a Chapter 6: AN ANALYSIS OF EVOLUTIONARY-BASED SAMPLING METHODOLOGIESAbstract; 1. Introduction; 2. Background; 3. Numerical Experiments: Design and Implementation; 4. Results and Discussion; 5. Conclusion; References; Blank Page; INDEX. | |
| 520 | |a A common approach for solving simulation-driven engineering problems is by using metamodel-assisted optimization algorithms, namely, in which a metamodel approximates the computationally expensive simulation and provides predicted values at a lower computational cost. Such algorithms typically generate an initial sample of solutions which are then used to train a preliminary metamodel and to initiate an optimization process. One approach for generating the initial sample is with the design of experiment methods which are statistically oriented, while the more recent search-driven sampling appr. | ||
| 590 | |a eBooks on EBSCOhost |b EBSCO eBook Subscription Academic Collection - Worldwide | ||
| 650 | 0 | |a Evolutionary computation. | |
| 650 | 0 | |a Engineering mathematics. | |
| 650 | 6 | |a Réseaux neuronaux à structure évolutive. | |
| 650 | 6 | |a Mathématiques de l'ingénieur. | |
| 650 | 7 | |a COMPUTERS |x General. |2 bisacsh | |
| 650 | 7 | |a Engineering mathematics |2 fast | |
| 650 | 7 | |a Evolutionary computation |2 fast | |
| 700 | 1 | |a Washington, Sean. | |
| 776 | 0 | 8 | |i Print version: |t New developments in evolutionary computation research |z 9781634634939 |w (DLC) 2014042395 |w (OCoLC)897042180 |
| 830 | 0 | |a Computer science, technology and applications. | |
| 856 | 4 | 0 | |u https://ebsco.uam.elogim.com/login.aspx?direct=true&scope=site&db=nlebk&AN=948063 |z Texto completo |
| 938 | |a ProQuest Ebook Central |b EBLB |n EBL2081023 | ||
| 938 | |a EBSCOhost |b EBSC |n 948063 | ||
| 938 | |a YBP Library Services |b YANK |n 12148052 | ||
| 994 | |a 92 |b IZTAP | ||