Bibliografische Daten
ISBN/EAN: 9781441941237
Sprache: Englisch
Umfang: xvi, 338 S., 200 s/w Illustr., 338 p. 200 illus.
Einband: kartoniertes Buch
Beschreibung
InhaltsangabeContributing Authors.- Preface.- Foreword.- Genetic Programming: Theory and Practice.- Genome-Wide Genetic Analysis Using Genetic Programming: The Critical Need for Expert Knowledge.- Lifting the Curse of Dimensionality.- Genetic Programming for Classifying Cancer Data and Controlling Humanoid Robots.- Boosting Improves Stability and Accuracy of Genetic Programming in Biological Sequence Classification.- Othogonal Evoluton of Teams: A Class of Algorithms for Evolving Teams with Inversely Correlated Errors.- Multidimensional Tags, Cooperative Populations, and Genetic Programming.- Coevolving Fitness Models for Accelerating Evolution and Reducing Evaluations.- Multi-Domain Observations Concerning the Use of Genetic Programming to Automatically Synthesize Human-Competitive Designs for Analog Circuits, Optical Lens Systems, Controllers, Antennas, Mechanical Systems, and Quantum Computing Circuits.- Robust Pareto Front Genetic Programming Parameter Selection Based on Design of Experiments and Industrial Data.- Pursuing the Pareto Paradigm: Tournaments, Algorithm Variations and Ordinal Optimization.- Applying Genetic Programming to Reservoir History Matching Problem.- Comparison of Robustness of Three Filter Design Strategies Using Genetic Programming and Bond Graphs.- Design of Posynomial Models for Mosfets: Symbolic Regression Using Genetic Algorithms.- Phase Transitions in Genetic Programming Search.- Efficient Markov Chain Model of Machine Code Program Execution and Halting.- A Re-examination of a Real World Blood Flow Modeling Problem Using Context-aware Crossover.- Large-Scale, Time-Constrained Symbolic Regression.- Stock Selection: An Innovative Application of Genetic Programming Methodology.- Index.
Inhalt
Contributing Authors.- Preface.- Foreword.- Genetic Programming: Theory and Practice.- Genome-Wide Genetic Analysis Using Genetic Programming: The Critical Need for Expert Knowledge.- Lifting the Curse of Dimensionality.- Genetic Programming for Classifying Cancer Data and Controlling Humanoid Robots.- Boosting Improves Stability and Accuracy of Genetic Programming in Biological Sequence Classification.- Othogonal Evoluton of Teams: A Class of Algorithms for Evolving Teams with Inversely Correlated Errors.- Multidimensional Tags, Cooperative Populations, and Genetic Programming.- Coevolving Fitness Models for Accelerating Evolution and Reducing Evaluations.- Multi-Domain Observations Concerning the Use of Genetic Programming to Automatically Synthesize Human-Competitive Designs for Analog Circuits, Optical Lens Systems, Controllers, Antennas, Mechanical Systems, and Quantum Computing Circuits.- Robust Pareto Front Genetic Programming Parameter Selection Based on Design of Experiments and Industrial Data.- Pursuing the Pareto Paradigm: Tournaments, Algorithm Variations and Ordinal Optimization.- Applying Genetic Programming to Reservoir History Matching Problem.- Comparison of Robustness of Three Filter Design Strategies Using Genetic Programming and Bond Graphs.- Design of Posynomial Models for Mosfets: Symbolic Regression Using Genetic Algorithms.- Phase Transitions in Genetic Programming Search.- Efficient Markov Chain Model of Machine Code Program Execution and Halting.- A Re-examination of a Real World Blood Flow Modeling Problem Using Context-aware Crossover.- Large-Scale, Time-Constrained Symbolic Regression.- Stock Selection: An Innovative Application of Genetic Programming Methodology.- Index.