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在“
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”中,
命中:
19,304
条,耗时:0.1229463 秒
在所有数据库中总计命中:
37,204
条
1.
Dynamic R-parameter based integrated model predictive iterative
learning
control for batch
process
es
作者:
Li Jia
a
;
jiali@staff.shu.end.cn
;
Chao Han
a
;
Min-sen Chiu
b
;
checms@nus.edu.sg
关键词:
Batch
process
;
Integrated
learning
control
;
Iterative
learning
control (ILC)
;
Model predictive control (MPC)
;
Model identification
;
Dynamic R-parameter
刊名:Journal of
Process
Control
出版年:2017
2.
The impact of instituting
Process
-Oriented Guided-Inquiry
Learning
(POGIL) in a fundamental nursing course
作者:
Maureen C. Roller
;
roller@adelphi.edu
;
Susan Zori
szori@adelphi.edu
关键词:
Group case studies
;
Active
learning
;
Process
-Oriented Guided Inquiry
Learning
research (POGIL)
;
Fundamental nursing course
;
Critical thinking
刊名:Nurse Education Today
出版年:2017
3.
Semi-supervised selective ensemble
learning
based on distance to model for nonlinear soft sensor development
作者:
Weiming Shao
swmupc@163.com
Author Vitae
;
Xuemin Tian
;
tianxm@upc.edu.cn
Author Vitae
关键词:
Nonlinear soft sensor
;
Semi-supervised ensemble
learning
;
Selective ensemble
learning
;
Distance to model
;
Adaptive
process
state partition
;
Particle swarm optimization
刊名:Neurocomputing
出版年:2017
4.
Informal
learning
process
es in support of clinical service delivery in a service-oriented community pharmacy
作者:
Brandon J. Patterson
;
Pharm.D.
;
Ph.D.
a
;
e
;
Brianne K. Bakken
;
Pharm.D.
b
;
f
;
William R. Doucette
;
Ph.D.
c
;
william-doucette@uiowa.edu
;
Julie M. Urmie
;
Ph.D.
c
;
Randal P. McDonough
;
Pharm.D.
;
M.S.
d
关键词:
Informal
learning
;
Community pharmacy
;
Pharmacy technician
;
Clinical pharmacy services
刊名:Research in Social and Administrative Pharmacy
出版年:2017
5.
Learning
FCMs with multi-local and balanced memetic algorithms for forecasting industrial drying
process
es
作者:
Jose L. Salmeron
a
;
b
;
c
;
salmeron@acm.org
Author Vitae
;
Antonio Ruiz-Celma
d
;
antoniorcelma@gmail.com
Author Vitae
;
Angel Mena
e
Author Vitae
关键词:
Fuzzy
;
Cognitive MapsMachine
learning
;
Industrial drying
;
Memetic algorithm
刊名:Neurocomputing
出版年:2017
6.
Conceptualizing impact assessment as a
learning
process
作者:
Luis E. Sá
;
nchez
a
;
lsanchez@usp.br
Author Vitae
;
Ross Mitchell
b
;
ross.mitchell@ualberta.net
Author Vitae
关键词:
Effectiveness
;
Environmental assessment
;
Knowledge management
;
Organizational
learning
;
Social
learning
刊名:Environmental Impact Assessment Review
出版年:2017
7.
An ANN approach for modeling the multisource yield
learning
process
with semiconductor manufacturing as an example
作者:
Toly Chen
tolychen@ms37.hinet.net
关键词:
Yield
;
Learning
;
Semiconductor
;
Artificial neural network
刊名:Computers & Industrial Engineering
出版年:2017
8.
Robust
learning
in SpikeProp
作者:
Sumit Bam Shrestha
bam_sumit@hotmail.com
sumitbam001@e.ntu.edu.sg
;
Qing Song
;
eqsong@ntu.edu.sg
关键词:
Spiking Neural Network
;
Error analysis
;
Weight convergence
;
Robust stability
;
Supervised
learning
;
Adaptive
learning
rate
刊名:Neural Networks
出版年:2017
9.
Uniform stable radial basis function neural network for the prediction in two mechatronic
process
es
作者:
José
;
de Jesú
;
s Rubio
;
jrubioa@ipn.mx
;
rubio.josedejesus@gmail.com
Author Vitae
;
Israel EliasAuthor Vitae
;
David Ricardo CruzAuthor Vitae
;
Jaime PachecoAuthor Vitae
关键词:
Radial basis function neural network
;
Stability
;
Learning
;
Mechatronic
process
刊名:Neurocomputing
出版年:2017
10.
Individual contributions in student-led collaborative
learning
: Insights from two analytical approaches to explain the quality of group outcome
作者:
Simone Volet
a
;
S.Volet@murdoch.edu.au
;
Marja Vauras
b
;
c
;
marja.vauras@utu.fi
;
Anne-Elina Salo
c
;
anne-elina.salo@utu.fi
;
Deep Khosa
d
;
dkhosa@uoguelph.ca
关键词:
Co-construction
;
Socially shared metacognitive regulation
;
Collaborative
learning
;
Process
data analysis
;
Role analysis
刊名:
Learning
and Individual Differences
出版年:2017
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