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Titlebook: Astroparticle Physics; Claus Grupen Textbook 20051st edition Springer-Verlag Berlin Heidelberg 2005 Astronomy.Astrophysics.Big Bang.Cosmic

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期刊全称Astroparticle Physics
影响因子2023Claus Grupen
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发行地址Introductory text which does not overload the reader.Most recent results are included e.g. neutrino-astronomy.Update of the German edition.Delivers an orientation for beginners in astroparticle physic
图书封面Titlebook: Astroparticle Physics;  Claus Grupen Textbook 20051st edition Springer-Verlag Berlin Heidelberg 2005 Astronomy.Astrophysics.Big Bang.Cosmic
影响因子The book describes the branch of astrophysics in which processes in the universe are investigated with experimental methods known from particle physics experiments. After a historical introduction to the basics of elementary particles, their interactions and the relevant detection techniques are described. The main body of the book concerns cosmic rays. The modern aspects of astroparticle physics are described in a chapter on cosmology. The book provides an orientation in the field of astroparticle physics that many beginners might look for. The physics issues are presented with little mathematics, and the results are illustrated by many diagrams. The reader has a chance to enter this field of astrophysics with a book that closes the gap between expert and popular level.
Pindex Textbook 20051st edition
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elivers an orientation for beginners in astroparticle physicThe book describes the branch of astrophysics in which processes in the universe are investigated with experimental methods known from particle physics experiments. After a historical introduction to the basics of elementary particles, thei
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Textbook 20051st editions experiments. After a historical introduction to the basics of elementary particles, their interactions and the relevant detection techniques are described. The main body of the book concerns cosmic rays. The modern aspects of astroparticle physics are described in a chapter on cosmology. The book
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A Hybrid Algorithm for Stochastic Multiobjective Programming Problempercube Sampling, Monte Carlo simulation, Support Vector Regression and Artificial Bee Colony algorithm. Several numerical examples are presented to illustrate the validity and performance of the hybrid algorithm. The results suggest that the proposed algorithm is very suitable for solving stochastic multiobjective programming problem.
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