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IISER-KIndian Institute of Science Education & Research - Kolkata
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Record 5 of 15
You searched IISERK - Subject: Sampling (Statistics)
Tag In 1 In 2 Data
001  vtls000037052
003  IISER-K
005  20220801113000.0
007  cr nn 008mamaa
008  220801s2021 sz | s |||| 0|eng d
020  \a 9783030728199 \9 978-3-030-72819-9
035  \a (DE-He213)978-3-030-72819-9
039 9\y 202208011130 \z Siladitya
050 4\a QA276.4-.45
08204\a 519.5 \2 23
1001 \a Cortez, Paulo. \e author. \4 aut \4 http://id.loc.gov/vocabulary/relators/aut
24510\a Modern Optimization with R \h [electronic resource] / \c by Paulo Cortez.
250  \a 2nd ed. 2021.
264 1\a Cham : \b Springer International Publishing : \b Imprint: Springer, \c 2021.
300  \a XVII, 254 p. 43 illus. \b online resource.
336  \a text \b txt \2 rdacontent
337  \a computer \b c \2 rdamedia
338  \a online resource \b cr \2 rdacarrier
347  \a text file \b PDF \2 rda
4901 \a Use R!, \x 2197-5744
5050 \a Chapter 1. introduction -- Chapter 2. R. Basics -- Chapter 3. Blind Search -- Chapter 4. Local Search -- Chapter 5. Population Based Search -- Chapter 6. Multi-Object Optimization.
520  \a The goal of this book is to gather in a single document the most relevant concepts related to modern optimization methods, showing how such concepts and methods can be addressed using the open source, multi-platform R tool. Modern optimization methods, also known as metaheuristics, are particularly useful for solving complex problems for which no specialized optimization algorithm has been developed. These methods often yield high quality solutions with a more reasonable use of computational resources (e.g. memory and processing effort). Examples of popular modern methods discussed in this book are: simulated annealing; tabu search; genetic algorithms; differential evolution; and particle swarm optimization. This book is suitable for undergraduate and graduate students in Computer Science, Information Technology, and related areas, as well as data analysts interested in exploring modern optimization methods using R. This new edition integrates the latest R packages through text and code examples. It also discusses new topics, such as: the impact of artificial intelligence and business analytics in modern optimization tasks; the creation of interactive Web applications; usage of parallel computing; and more modern optimization algorithms (e.g., iterated racing, ant colony optimization, grammatical evolution). .
650 0\a Mathematical statistics—Data processing.
650 0\a Mathematical optimization.
650 0\a Artificial intelligence—Data processing.
650 0\a Sampling (Statistics).
650 0\a Artificial intelligence.
650 0\a Programming languages (Electronic computers).
65014\a Statistics and Computing.
65024\a Optimization.
65024\a Data Science.
65024\a Methodology of Data Collection and Processing.
65024\a Artificial Intelligence.
65024\a Programming Language.
7102 \a SpringerLink (Online service)
7730 \t Springer Nature eBook
77608\i Printed edition: \z 9783030728182
77608\i Printed edition: \z 9783030728205
830 0\a Use R!, \x 2197-5744
85640\u https://doi.org/10.1007/978-3-030-72819-9
912  \a ZDB-2-SMA
912  \a ZDB-2-SXMS
950  \a Mathematics and Statistics (SpringerNature-11649)
950  \a Mathematics and Statistics (R0) (SpringerNature-43713)

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