Information Processing with Evolutionary Algorithms From Industrial Applications to Academic Speculations 1st Edition by Manuel Grana, ‎Richard J Duro, ‎Alicia d Anjou ISBN 9781846281174 by Manuel Grana (editor), Richard Duro (editor), Alicia D'anjou (editor), Paul P. Wang (editor) 9781846281174, 9781852338664, 1846281172, 1852338660 instant download after payment.

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ISBN 13: 9781846281174
Author: Manuel Grana, ‎Richard J Duro, ‎Alicia d Anjou

The last decade of the 20th century has witnessed a surge of interest in num- ical, computation-intensive approaches to information processing. The lines that draw the boundaries among statistics, optimization, arti cial intelligence and information processing are disappearing, and it is not uncommon to nd well-founded and sophisticated mathematical approaches in application - mains traditionally associated with ad-hoc programming. Heuristics has - come a branch of optimization and statistics. Clustering is applied to analyze soft data and to provide fast indexing in the World Wide Web. Non-trivial matrix algebra is at the heart of the last advances in computer vision. The breakthrough impulse was, apparently, due to the rise of the interest in arti cial neural networks, after its rediscovery in the late 1980s. Disguised as ANN, numerical and statistical methods made an appearance in the - formation processing scene, and others followed. A key component in many intelligent computational processing is the search for an optimal value of some function. Sometimes, this function is not evident and it must be made explicit in order to formulate the problem as an optimization problem. The search - ten takes place in high-dimensional spaces that can be either discrete, or c- tinuous or mixed. The shape of the high-dimensional surface that corresponds to the optimized function is usually very complex. Evolutionary algorithms are increasingly being applied to information processing applications that require any kind of optimization.

Information Processing with Evolutionary Algorithms From Industrial Applications to Academic Speculations 1st Table of contents:

1. Adaptive Business Intelligence Based on Evolution Strategies: Some Application Examples of Self-Adaptive Software – T. Bäck

2. Extending the Boundaries of Design Optimization by Integrating Fast Optimization Techniques with Machine Code Based, Linear Genetic Programming – L. M. Deschaine, F.D. Francone

3. Evolutionary Optimization of Approximating Triangulations for Surface Reconstruction from Unstructured 3D Data – K. Weinert, J. Mehnen, M. Schneider

4. An Evolutionary Algorithm Based on Morphological Associative Memories for Endmember Selection in Hyperspectral Images – M. Graña, C. Hernandez, A. d’Anjou

5. On a Gradient-based Evolution Strategy for Parametric Illumination Correction – Elsa Fernández, Manuel Graña, Jesús Ruiz-Cabello

6. A New Chromosome Codification for Scheduling Problems – Ramiro Varela, Camino R. Vela, Jorge Puente, David Serrano, Ana Suárez

7. Evolution-based Learning of Ontological Knowledge for a Large-scale Multi-agent Simulation – A. Lazar, R.G. Reynolds

8. An Evolutionary Algorithms Approach to Phylogenetic Tree Construction – C. B. Congdon

9. Robot Controller Evolution with Macroevolutionary Algorithms – J. A. Becerra, J. Santos, R.J. Duro

10. Evolving Natural Language Grammars – W. Cyre

11. Evaluating Protein Structure Prediction Models with Evolutionary Algorithms – J. Gamalielsson, B. Olsson

12. Learning Decision Rules by Means of Hybrid-Encoded Evolutionary Algorithms – J.C. Riquelme, J.S. Aguilar-Ruiz

13. Evolvable Hardware Techniques for Gate-Level Synthesis of Combinational Circuits – A. Hernández-Aguirre

14. The Evolutionary Learning Rule in System Identification – Oscar Montiel, Oscar Castillo, Patricia Melin, Roberto Sepulveda

15. Current and Future Research Trends in Evolutionary Multiobjective Optimization – C. A. Coello Coello, G. Toscano Pulido, E. Mezura Montes

16. Genetic Algorithms with Limited Convergence – J. Kubalík, L. Rothkrantz, J. Lažanský

17. Evolution with Sampled Fitness Functions – F. Bellas, J. A. Becerra, R. J. Duro

18. Molecular Computing by Signaling Pathways – J.-Q. Liu, K. Shimohara

19. Strategy-Oriented Evolutionary Games: Toward a Grammatical Model of Games – B. Cases, S.O. Anchorena

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Tags: Manuel Grana, Richard J Duro, Alicia d Anjou, Processing, Evolutionary