語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Imputation methods for missing hydrometeorological data estimation
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Imputation methods for missing hydrometeorological data estimation/ by Ramesh S.V. Teegavarapu.
作者:
Teegavarapu, Ramesh S. V.
出版者:
Cham :Springer International Publishing : : 2024.,
面頁冊數:
xvii, 517 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:
Springer Nature eBook
標題:
Statistical matching. -
電子資源:
https://doi.org/10.1007/978-3-031-60946-6
ISBN:
9783031609466
Imputation methods for missing hydrometeorological data estimation
Teegavarapu, Ramesh S. V.
Imputation methods for missing hydrometeorological data estimation
[electronic resource] /by Ramesh S.V. Teegavarapu. - Cham :Springer International Publishing :2024. - xvii, 517 p. :ill. (some col.), digital ;24 cm. - Water science and technology library,v. 1081872-4663 ;. - Water science and technology library ;v.66..
Introduction to Missing Data -- Methods for Imputation of Missing Data -- Temporal Interpolation Methods -- Spatial Interpolation Methods -- Data Driven Modes for Imputation -- Multiple Imputation Methods -- Evaluation of Methods and Imputed Data.
This book serves as a unique reference that provides a comprehensive discussion about the state-of-the-art spatial and temporal, statistical, and data mining methods for imputation of missing hydrometeorological data. The primary audience for this book are researchers, scientists, graduate-level and higher students, modelers, data scientists working in hydrological, meteorological, climatological, and earth sciences. Data analysts in other disciplines will also be interested in this book. The book appeals to graduate students, researchers in civil and environmental engineering, geosciences, climatology, and hydrological and data sciences. It will be an ideal reference book for state and federal agencies that collect and process hydrometeorological and climatological data. Engineering professionals, hydrologists, meteorologists, and data and spatial analysts dealing with large hydrometeorological datasets. Researchers and modelers involve in the development of long-term datasets at national and international institutions.
ISBN: 9783031609466
Standard No.: 10.1007/978-3-031-60946-6doiSubjects--Topical Terms:
562781
Statistical matching.
LC Class. No.: GB2801.72.S7
Dewey Class. No.: 551.57
Imputation methods for missing hydrometeorological data estimation
LDR
:02378nam a2200337 a 4500
001
1133841
003
DE-He213
005
20240720125228.0
006
m d
007
cr nn 008maaau
008
241213s2024 sz s 0 eng d
020
$a
9783031609466
$q
(electronic bk.)
020
$a
9783031609459
$q
(paper)
024
7
$a
10.1007/978-3-031-60946-6
$2
doi
035
$a
978-3-031-60946-6
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
GB2801.72.S7
072
7
$a
RBK
$2
bicssc
072
7
$a
SCI081000
$2
bisacsh
072
7
$a
RBK
$2
thema
082
0 4
$a
551.57
$2
23
090
$a
GB2801.72.S7
$b
T258 2024
100
1
$a
Teegavarapu, Ramesh S. V.
$3
1455087
245
1 0
$a
Imputation methods for missing hydrometeorological data estimation
$h
[electronic resource] /
$c
by Ramesh S.V. Teegavarapu.
260
$a
Cham :
$c
2024.
$b
Springer International Publishing :
$b
Imprint: Springer,
300
$a
xvii, 517 p. :
$b
ill. (some col.), digital ;
$c
24 cm.
490
1
$a
Water science and technology library,
$x
1872-4663 ;
$v
v. 108
505
0
$a
Introduction to Missing Data -- Methods for Imputation of Missing Data -- Temporal Interpolation Methods -- Spatial Interpolation Methods -- Data Driven Modes for Imputation -- Multiple Imputation Methods -- Evaluation of Methods and Imputed Data.
520
$a
This book serves as a unique reference that provides a comprehensive discussion about the state-of-the-art spatial and temporal, statistical, and data mining methods for imputation of missing hydrometeorological data. The primary audience for this book are researchers, scientists, graduate-level and higher students, modelers, data scientists working in hydrological, meteorological, climatological, and earth sciences. Data analysts in other disciplines will also be interested in this book. The book appeals to graduate students, researchers in civil and environmental engineering, geosciences, climatology, and hydrological and data sciences. It will be an ideal reference book for state and federal agencies that collect and process hydrometeorological and climatological data. Engineering professionals, hydrologists, meteorologists, and data and spatial analysts dealing with large hydrometeorological datasets. Researchers and modelers involve in the development of long-term datasets at national and international institutions.
650
0
$a
Statistical matching.
$3
562781
650
0
$a
Hydrometeorology
$x
Statistical methods.
$3
1292899
650
0
$a
Mathematical statistics.
$3
527941
650
1 4
$a
Water.
$3
569476
650
2 4
$a
Statistics.
$3
556824
650
2 4
$a
Data Mining and Knowledge Discovery.
$3
677765
650
2 4
$a
Data Engineering.
$3
1226308
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
830
0
$a
Water science and technology library ;
$v
v.66.
$3
888691
856
4 0
$u
https://doi.org/10.1007/978-3-031-60946-6
950
$a
Earth and Environmental Science (SpringerNature-11646)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入