Fr. 239.00

Numerical and Evolutionary Optimization - NEO 2017

Englisch · Taschenbuch

Versand in der Regel in 6 bis 7 Wochen

Beschreibung

Mehr lesen

This book features 15 chapters based on the Numerical and Evolutionary Optimization (NEO 2017) workshop, held from September 27 to 29 in the city of Tijuana, Mexico. The event gathered researchers from two complimentary fields to discuss the theory, development and application of state-of-the-art techniques to address search and optimization problems. The lively event included 7 invited talks and 64 regular talks covering a wide range of topics, from evolutionary computer vision and machine learning with evolutionary computation, to set oriented numeric and steepest descent techniques. Including research submitted by the NEO community, the book provides informative and stimulating material for future research in the field.

Inhaltsverzeichnis

Deterministic Parameter Control in Differential Evolution with Combined Variants for Constrained Search Spaces.- A Descent Method for Equality and Inequality Constrained Multiobjective Optimization Problems.- Evaluating Memetic Building Spatial Design Optimisation Using Hypervolume Indicator Gradient Ascent.- Fitting Multiple Ellipses with PEARL and a Multi-objective Genetic Algorithm.- Analyzing Evolutionary Art Audience Interaction by Means of a Kinect Based Non-Intrusive Method.- Applying Control Theory to Optimize the Inventory Holding Costs in Supply Chains.- On the Selection of Tuning Parameters in Predictive Controllers Based on NSGA-II.- IDA-PBC Controller Tuning Using Steepest Descent.- Self-Tuning for a SISO-Type Fuzzy Control Based on the Relay Feedback Approach.- Optimal Design Of Sliding Mode Control Combined with Positive Position Feedback.- Biot's Parameters Estimation In Ultrasound Propagation Through Cancellous Bone.- Optimal Sizing of Low-DropOut Voltage Regulators by NSGA-II and PVT Analysis.- Genetic Optimization of Fuzzy Systems for the Classification of Treated Water Quality.- Stabilization Based on Fuzzy System for Structures Affected by External Disturbances.- Comparison of Two Methods for I/Q Imbalance Compensation Applied in RF Power Amplifiers.- An Application of Data Envelopment Analysis to the Performance Assessment of Online Social Networks Usage in Mazatlan Hotel Organizations. 

Zusammenfassung

This book features 15 chapters based on the Numerical and Evolutionary Optimization (NEO 2017) workshop, held from September 27 to 29 in the city of Tijuana, Mexico. The event gathered researchers from two complimentary fields to discuss the theory, development and application of state-of-the-art techniques to address search and optimization problems. The lively event included 7 invited talks and 64 regular talks covering a wide range of topics, from evolutionary computer vision and machine learning with evolutionary computation, to set oriented numeric and steepest descent techniques. Including research submitted by the NEO community, the book provides informative and stimulating material for future research in the field.

Produktdetails

Mitarbeit Yazmin Maldonado (Herausgeber), Yazmin Maldonado et al (Herausgeber), Olive Schütze (Herausgeber), Oliver Schütze (Herausgeber), Leonardo Trujillo (Herausgeber), Paul Valle (Herausgeber)
Verlag Springer, Berlin
 
Sprache Englisch
Produktform Taschenbuch
Erschienen 01.01.2018
 
EAN 9783030071448
ISBN 978-3-0-3007144-8
Seiten 312
Abmessung 155 mm x 17 mm x 235 mm
Gewicht 504 g
Illustration XIV, 312 p. 137 illus.
Serie Studies in Computational Intelligence
Themen Naturwissenschaften, Medizin, Informatik, Technik > Technik > Allgemeines, Lexika

C, Artificial Intelligence, engineering, Computational Intelligence, Evolutionary Optimization, Search and Optimization Techniques

Kundenrezensionen

Zu diesem Artikel wurden noch keine Rezensionen verfasst. Schreibe die erste Bewertung und sei anderen Benutzern bei der Kaufentscheidung behilflich.

Schreibe eine Rezension

Top oder Flop? Schreibe deine eigene Rezension.

Für Mitteilungen an CeDe.ch kannst du das Kontaktformular benutzen.

Die mit * markierten Eingabefelder müssen zwingend ausgefüllt werden.

Mit dem Absenden dieses Formulars erklärst du dich mit unseren Datenschutzbestimmungen einverstanden.