語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Modern optimization with R
~
SpringerLink (Online service)
FindBook
Google Book
Amazon
博客來
Modern optimization with R
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Modern optimization with R/ by Paulo Cortez.
作者:
Cortez, Paulo.
出版者:
Cham :Springer International Publishing : : 2021.,
面頁冊數:
xvii, 254 p. :ill., digital ;24 cm.
內容註:
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.
Contained By:
Springer Nature eBook
標題:
R (Computer program language) -
電子資源:
https://link.springer.com/openurl.asp?genre=book&isbn=978-3-030-72819-9
ISBN:
9783030728199
Modern optimization with R
Cortez, Paulo.
Modern optimization with R
[electronic resource] /by Paulo Cortez. - Second edition. - Cham :Springer International Publishing :2021. - xvii, 254 p. :ill., digital ;24 cm. - Use R!,2197-5736. - Use R!..
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.
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)
ISBN: 9783030728199
Standard No.: 10.1007/978-3-030-72819-9doiSubjects--Topical Terms:
784593
R (Computer program language)
LC Class. No.: QA276.45.R3 / C67 2021
Dewey Class. No.: 519.50285
Modern optimization with R
LDR
:02567nmm a2200349 a 4500
001
2242325
003
DE-He213
005
20210730152316.0
006
m d
007
cr nn 008maaau
008
211207s2021 sz s 0 eng d
020
$a
9783030728199
$q
(electronic bk.)
020
$a
9783030728182
$q
(paper)
024
7
$a
10.1007/978-3-030-72819-9
$2
doi
035
$a
978-3-030-72819-9
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA276.45.R3
$b
C67 2021
072
7
$a
UFM
$2
bicssc
072
7
$a
COM077000
$2
bisacsh
072
7
$a
UFM
$2
thema
082
0 4
$a
519.50285
$2
23
090
$a
QA276.45.R3
$b
C828 2021
100
1
$a
Cortez, Paulo.
$3
2107028
245
1 0
$a
Modern optimization with R
$h
[electronic resource] /
$c
by Paulo Cortez.
250
$a
Second edition.
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2021.
300
$a
xvii, 254 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
Use R!,
$x
2197-5736
505
0
$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
R (Computer program language)
$3
784593
650
0
$a
Electronic data processing.
$3
520749
650
0
$a
Mathematical optimization.
$3
517763
650
1 4
$a
Statistics and Computing/Statistics Programs.
$3
894293
650
2 4
$a
Optimization.
$3
891104
650
2 4
$a
Data Structures and Information Theory.
$3
3382368
650
2 4
$a
Artificial Intelligence.
$3
769149
650
2 4
$a
Statistics, general.
$3
896933
650
2 4
$a
Professional Computing.
$3
3201325
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer Nature eBook
830
0
$a
Use R!.
$3
1306062
856
4 0
$u
https://link.springer.com/openurl.asp?genre=book&isbn=978-3-030-72819-9
950
$a
Mathematics and Statistics (SpringerNature-11649)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9403380
電子資源
11.線上閱覽_V
電子書
EB QA276.45.R3 C67 2021
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入