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中国地质文献-英文(439)
SpringerLink电子期刊(70489)
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在“
Elsevier电子期刊
”中,
命中:
118,138
条,耗时:小于0.01 秒
在所有数据库中总计命中:
201,452
条
1.
Pairing support vector algorithm for data
regression
作者:
Pei-Yi Hao
;
haupy@cc.kuas.edu.tw
Author Vitae
关键词:
Support vector
regression
;
Twin support vector
regression
;
Noise heteroscedastic model
;
Parametric insensitive model
;
Nonparallel functions
;
Sparse
regression
刊名:Neurocomputing
出版年:2017
2.
Empirical models for tool forces prediction of drag-typed picks based on principal component
regression
and ridge
regression
methods
作者:
Xiang Wang
a
;
b
;
Yunpei Liang
a
;
liangyunpei@cqu.edu.cn
;
Qingfeng Wang
b
;
Zhenyu Zhang
a
关键词:
Drag-typed picks
;
Tool forces
;
Empirical models
;
Regression
analysis
刊名:Tunnelling and Underground Space Technology
出版年:2017
3.
A robust and efficient stepwise
regression
method for building sparse polynomial chaos expansions
作者:
Simon Abraham
a
;
Simon.Abraham@ulb.ac.be
;
Mehrdad Raisee
b
;
Ghader Ghorbaniasl
a
;
Francesco Contino
a
;
Chris Lacor
a
关键词:
Uncertainty quantification
;
Regression
-based polynomial chaos
;
Sparse polynomial chaos expansion
;
Least angle
regression
;
Stepwise
regression
刊名:Journal of Computational Physics
出版年:2017
4.
Composite quantile
regression
for correlated data
作者:
Weihua Zhao
a
;
Heng Lian
b
;
henglian@cityu.edu.hk
;
Xinyuan Song
c
关键词:
Composite quantile
regression
;
Longitudinal data
;
Quadratic inference function
;
Weighted composite quantile
regression
刊名:Computational Statistics & Data Analysis
出版年:2017
5.
A multi-row deletion diagnostic for influential observations in small-sample
regression
s
作者:
Daniel T. Kaffine
a
;
daniel.kaffine@colorado.edu
;
Graham A. Davis
b
;
gdavis@mines.edu
关键词:
Regression
diagnostics
;
Multi-row deletion
;
Inference
;
Influence points
;
Outliers
;
Growth
regression
s
;
Institutions
;
Resource curse
刊名:Computational Statistics & Data Analysis
出版年:2017
6.
Influences of environmental factors on Si-based photovoltaic modules after longtime outdoor exposure by multiple
regression
analysis
作者:
Jakapan Chantana
;
jakapan@fc.ritsumei.ac.jp" class="auth_mail" title="E-mail the corresponding author
;
Aika Kamei
ro0002kf@ed.ritsumei.ac.jp" class="auth_mail" title="E-mail the corresponding author
;
Takashi Minemoto
minemoto@se.ritsumei.ac.jp" class="auth_mail" title="E-mail the corresponding author
关键词:
Multiple
regression
analysis
;
Standard partial
regression
coefficients
;
Outdoor performance
;
Environmental factors
;
Si-based photovoltaic modules
刊名:Renewable Energy
出版年:2017
7.
Automated segmentation and area estimation of neural foramina with boundary
regression
model
作者:
Xiaoxu He
a
;
b
;
xhe244@uwo.ca
Author Vitae
;
Andrea Lum
a
;
b
Author Vitae
;
Manas Sharma
a
;
b
Author Vitae
;
Gary Brahm
a
;
b
Author Vitae
;
Ashley Mercado
a
;
b
Author Vitae
;
Shuo Li
a
;
b
;
slishuo@gmail.com
Author Vitae
关键词:
Automated segmentation
;
Area estimation
;
Neural foramina stenosis
;
Boundary
regression
model
;
Multiple output support vector
regression
;
Multiple kernel learning
刊名:Pattern Recognition
出版年:2017
8.
A prediction model for spontaneous
regression
of cervical intraepithelial neoplasia grade 2, based on simple clinical parameters
作者:
Margot M. Koeneman
;
MD
a
;
b
;
margot.koeneman@mumc.nl
;
Freyja H.M. van Lint
;
MD
a
;
b
;
Sander M.J. van Kuijk
;
PhD
c
;
Luc J.M. Smits
;
PhD
d
;
Loes F.S. Kooreman
;
MD
;
PhD
e
;
Roy F.P.M. Kruitwagen
;
MD
;
PhD
a
;
b
;
Arnold J. Kruse
;
MD
;
PhD
a
;
b
关键词:
Prediction
;
CIN 2
;
Low-grade squamous intraepithelial lesion
;
Regression
;
Personalized management
刊名:Human Pathology
出版年:2017
9.
Interactions between cadmium and decabrominated diphenyl ether on blood cells count in rats—Multiple factorial
regression
analysis
作者:
Marijana Curcic
a
;
makitox@pharmacy.bg.ac.rs
;
Aleksandra Buha
a
;
Sanja Stankovic
b
;
Vesna Milovanovic
c
;
Zorica Bulat
a
;
Danijela Đukić-Ćosić
a
;
Evica Antonijević
a
;
Slavica Vučinić
d
;
Vesna Matović
a
;
Biljana Antonijevic
a
关键词:
Cadmium
;
Decabrominated diphenyl ether
;
Interactions
;
Multiple factorial
regression
刊名:Toxicology
出版年:2017
10.
Mapping mineral prospectivity using an extreme learning machine
regression
作者:
Yongliang Chen
a
;
chenyongliang2009@hotmail.com" class="auth_mail" title="E-mail the corresponding author
;
Wei Wu
b
关键词:
Extreme learning machine (ELM)
regression
;
Logistic
regression
;
Mineral prospectivity mapping
;
Receiver operating characteristic (ROC) curve
;
Area under the curve or AUC
;
Youden index
刊名:Ore Geology Reviews
出版年:2017
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