Übersicht			Auf mobile öffnen

Lieferstatus:	Auf Bestellung (Lieferzeit unbekannt)
Veröffentlichung:	März 2017
Genre:	Naturwissensch., Medizin, Technik
	Artificial Intelligence / B / Computational Intelligence / Computer Modelling / Computer modelling & simulation / computer science / Computer simulation / Computermodellierung und -simulation / engineering / Engineering economics / Engineering Economics, Organization, Logistics, Marketing / Engineering economy / Engineering# general / Industrial Management / Ingenieurswesen, Maschinenbau allgemein / Management of specific areas / Management und Managementtechniken / Mathematical optimization / multi-objective optimization / Optimierung / Optimization / Resource Planning / Simulation and Modeling / Swarm-Based Heuristics mehr...
ISBN:	9783319509198
EAN-Code:	9783319509198
Verlag:	Springer EN
Einband:	Gebunden
Sprache:	English
Serie:	#10 - Modeling and Optimization in Science and Technologies
Dimensionen:	H 235 mm / B 155 mm / D
Gewicht:	8926 gr
Seiten:	494
Illustration:	XXI, 494 p. 191 illus., 43 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen
Zus. Info:	EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025.
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

The book provides readers with a snapshot of the state of the art in the field of nature-inspired computing and its application in optimization. The approach is mainly practice-oriented: each bio-inspired technique or algorithm is introduced together with one of its possible applications. Applications cover a wide range of real-world optimization problems: from feature selection and image enhancement to scheduling and dynamic resource management, from wireless sensor networks and wiring network diagnosis to sports training planning and gene expression, from topology control and morphological filters to nutritional meal design and antenna array design. There are a few theoretical chapters comparing different existing techniques, exploring the advantages of nature-inspired computing over other methods, and investigating the mixing time of genetic algorithms. The book also introduces a wide range of algorithms, including the ant colony optimization, the bat algorithm, genetic algorithms, the collision-based optimization algorithm, the flower pollination algorithm, multi-agent systems and particle swarm optimization. This timely book is intended as a practice-oriented reference guide for students, researchers and professionals.