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马克思主义、列宁主义、毛泽东思想、邓小平理论(5)
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在“
自然资源管理
”中,
命中:
18
条,耗时:小于0.01 秒
1.
A Machine
Learning
Approach for the Mean Flow Velocity Prediction in Alluvial Channels
作者:
Vasileios Kitsikoudis
;
Epaminondas Sidiropoulos…
关键词:
Data
;
driven modeling
;
Flow resistance
;
Gravel
;
bed rivers
;
Machine
learning
;
Sand
;
bed rivers
;
Stage
;
discharge relation
刊名:Water Resources Management
出版者:Springer Netherlands
年:2015
2.
Rehabilitating mussel beds in Coffee Bay, South Africa: Towards fostering cooperative small-scale fisheries governance and enabling community upliftment
作者:
Gurutze Calvo-Ugarteburu
;
Serge Raemaekers
;
Christina Halling
关键词:
Community upliftment
;
Fisheries governance
;
Mussel rehabilitation
;
Perna perna
;
Small
;
scale fisheries
刊名:Ambio
出版者:Springer Netherlands
年:2017
3.
Hybrid intelligent systems in petroleum reservoir characterization and modeling: the journey so far and the challenges ahead
作者:
Fatai Adesina Anifowose
;
Jane Labadin…
关键词:
Hybrid intelligent systems
;
Reservoir characterization and modeling
;
Petroleum reservoir properties
;
Computational intelligence
刊名:Journal of Petroleum Exploration and Production Technology
出版者:Springer Berlin Heidelberg
年:2017
4.
Metabolic Burden: Cornerstones in Synthetic Biology and Metabolic Engineering Applications
作者:
Gang Wu1
;
Qiang Yan2
;
J. Andrew Jones3
;
5
;
Yinjie J. Tang1
;
yinjie.tang@wustl.edu" class="auth_mail" title="E-mail the corresponding author
;
Stephen S. Fong2
;
ssfong@vcu.edu" class="auth_mail" title="E-mail the corresponding author
;
Mattheos A.G. Koffas3
;
4
;
5
;
koffam@rpi.edu" class="auth_mail" title="E-mail the corresponding author
关键词:
13C-MFA
;
genome-scale model
;
machine
learning
;
chromosomal engineering
刊名:Trends in Biotechnology
年:2016
5.
Data-driven methods to improve baseflow prediction of a regional groundwater model
作者:
Tianfang Xu
;
txu3@illinois.edu" class="auth_mail" title="E-mail the corresponding author
;
Albert J. Valocchi
关键词:
Statistical
learning
;
Baseflow
;
Predictive error
刊名:Computers & Geosciences
年:2015
6.
Predictive modeling of groundwater nitrate pollution using Random Forest and multisource variables related to intrinsic and specific vulnerability: A case study in an agricultural setting (Southern Spain)
作者:
Victor Rodriguez-Galianoa
;
vrgaliano@ugr.es" class="auth_mail
;
Maria Paula Mendesb
;
Maria Jose Garcia-Soldadoc
;
Mario Chica-Olmoc
;
Luis Ribeirob
关键词:
Random Forest
;
Groundwater
;
Vulnerability assessment
;
Machine
learning
techniques
;
Nitrates
刊名:Science of the Total Environment
年:1 April, 2014
7.
Spam detection using Random Boost
作者:
Dave DeBarr
;
ddebarr@gmu.edu
;
dave.debarr@microsoft.com
;
Harry Wechsler wechsler@gmu.edu
关键词:
Spam detection
;
Robust
learning
;
Random Boost
;
Random projection
;
Logit Boost
;
Random Forest
刊名:Pattern Recognition Letters
年:2012
8.
Using ADABOOST and Rough Set Theory for Predicting Debris Flow Disaster
作者:
Ping-Feng Pai (1) Lan-Lin Li (1) Wei-Zhan Hung (2) Kuo-Ping Lin (3)
关键词:
Debris flow
;
ADABOOST
;
Rough set theory
;
Prediction
;
Rule generation
刊名:Water Resources Management
年:2014
9.
Multiobjective Memetic Algorithm Applied to the Optimisation of Water Distribution Systems
作者:
Euan Barlow (1) Tiku T. Tanyimboh (1)
关键词:
Penalty
;
free memetic algorithm
;
Multi
;
objective optimisation
;
Water distribution system design
;
Parallel computing
;
High performance computing
;
Search space reduction
刊名:Water Resources Management
年:2014
10.
Case studies of scenario analysis for adaptive management of natural resource and infrastructure systems
作者:
Michelle C. Hamilton
;
Shital A. Thekdi…
关键词:
Scenario analysis
;
Risk analysis
;
Decision analysis
;
Sustainability
;
Adaptive management
;
Water resource management
;
Energy infrastructure
;
Infrastructure corridors
;
Climate change
刊名:Environment Systems and Decisions
出版者:Springer US
年:2013
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