Intelligent Astrophysics: Emergence, Complexity and Computation, cartea 39
Editat de Ivan Zelinka, Massimo Brescia, Dalya Baronen Limba Engleză Paperback – 16 apr 2022
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Specificații
ISBN-13: 9783030658694
ISBN-10: 3030658694
Ilustrații: VIII, 296 p. 126 illus., 108 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.43 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seria Emergence, Complexity and Computation
Locul publicării:Cham, Switzerland
ISBN-10: 3030658694
Ilustrații: VIII, 296 p. 126 illus., 108 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.43 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seria Emergence, Complexity and Computation
Locul publicării:Cham, Switzerland
Cuprins
Table of Contents will be included as soon as we receive the manuscript.
Textul de pe ultima copertă
This present book discusses the application of the methods to astrophysical data from different perspectives. In this book, the reader will encounter interesting chapters that discuss data processing and pulsars, the complexity and information content of our universe, the use of tessellation in astronomy, characterization and classification of astronomical phenomena, identification of extragalactic objects, classification of pulsars and many other interesting chapters. The authors of these chapters are experts in their field and have been carefully selected to create this book so that the authors present to the community a representative publication that shows a unique fusion of artificial intelligence and astrophysics.
Caracteristici
Presents new developments, advancements, and selected topics in the fields of artificial intelligence and related algorithms in the astrophysical data processing Discusses new ideas and interdisciplinary insight on the mutual intersection of subareas of artificial intelligence and computation and its impact and limits to many astrophysical problems Focuses on all aspects of reality-based computation approaches from an interdisciplinary point of view in all important areas of astrophysics as the signal processing in the radio astronomy, image processing with machine learning, deep learning applications on various astrophysical tasks, evolutionary computation in classification and modeling of astrophysical events, archive processing and anomaly detection in live streams from robotic telescopes and more