Cyclosporine concentration prediction using clustering and support vector regression methods

G. Camps-Valls; E. Soria-Olivas; J.J. Pérez-Ruixo; F. Pérez-Cruz; A.R. Figueiras-Vidal; A. Artés-Rodrı́guez

doi:10.1049/el:20020354

Cyclosporine concentration prediction using clustering and support vector regression methods

Electronics Letters ◽

10.1049/el:20020354 ◽

2002 ◽

Vol 38 (12) ◽

pp. 568 ◽

Cited By ~ 9

Author(s):

G. Camps-Valls ◽

E. Soria-Olivas ◽

J.J. Pérez-Ruixo ◽

F. Pérez-Cruz ◽

A.R. Figueiras-Vidal ◽

...

Keyword(s):

Support Vector Regression ◽

Support Vector ◽

Regression Methods ◽

Concentration Prediction

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A Comparative Study of Ensemble Support Vector Regression Methods for Short-term Load Forecasting

2018 5th International Conference on Systems and Informatics (ICSAI) ◽

10.1109/icsai.2018.8599332 ◽

2018 ◽

Cited By ~ 1

Author(s):

Jianhua Ye ◽

Li Yang

Keyword(s):

Comparative Study ◽

Support Vector Regression ◽

Load Forecasting ◽

Support Vector ◽

Short Term ◽

Regression Methods ◽

Short Term Load Forecasting

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A hybrid of Random Forest and Deep Auto-Encoder with support vector regression methods for accuracy improvement and uncertainty reduction of long-term streamflow prediction

Journal of Hydrology ◽

10.1016/j.jhydrol.2020.125717 ◽

2020 ◽

pp. 125717

Author(s):

Mahdi Abbasi ◽

Ashkan Farokhnia ◽

Masoud Bahreinimotlagh ◽

Reza Roozbahani

Keyword(s):

Random Forest ◽

Support Vector Regression ◽

Uncertainty Reduction ◽

Support Vector ◽

Streamflow Prediction ◽

Accuracy Improvement ◽

Regression Methods

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Extreme learning machine and swarm-based support vector regression methods for predicting crystal lattice parameters of pseudo-cubic/cubic perovskites

Journal of Applied Physics ◽

10.1063/5.0008809 ◽

2020 ◽

Vol 127 (24) ◽

pp. 245107

Author(s):

Taoreed O. Owolabi

Keyword(s):

Crystal Lattice ◽

Support Vector Regression ◽

Extreme Learning Machine ◽

Lattice Parameters ◽

Support Vector ◽

Regression Methods ◽

Learning Machine ◽

Crystal Lattice Parameters

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Energy Prediction for EVs Using Support Vector Regression Methods

Advances in Intelligent Systems and Computing - Intelligent Systems'2014 ◽

10.1007/978-3-319-11310-4_67 ◽

2015 ◽

pp. 769-780 ◽

Cited By ~ 1

Author(s):

Stefan Grubwinkler ◽

Markus Lienkamp

Keyword(s):

Support Vector Regression ◽

Support Vector ◽

Energy Prediction ◽

Regression Methods

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PM2.5 Concentration Prediction Based on Markov Blanke Feature Selection and Hybrid Kernel Support Vector Regression Optimized by Particle Swarm Optimization

Aerosol and Air Quality Research ◽

10.4209/aaqr.200144 ◽

2021 ◽

Vol 21 ◽

Author(s):

Lian-Hua Zhang ◽

Ze-Hong Deng ◽

Wen-Bo Wang

Keyword(s):

Feature Selection ◽

Particle Swarm Optimization ◽

Support Vector Regression ◽

Particle Swarm ◽

Support Vector ◽

Swarm Optimization ◽

Concentration Prediction ◽

Pm2.5 Concentration ◽

Hybrid Kernel

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The Estimation of Turkey's Energy Demand Through Artificial Neural Networks and Support Vector Regression Methods

Alphanumeric Journal ◽

10.17093/alphanumeric.756651 ◽

2020 ◽

Author(s):

Mehmet KAYAKUŞ

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Support Vector Regression ◽

Energy Demand ◽

Support Vector ◽

Regression Methods ◽

Artificial Neural

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Top corner gas concentration prediction using t‐distributed Stochastic Neighbor Embedding and Support Vector Regression algorithms

Concurrency and Computation Practice and Experience ◽

10.1002/cpe.5705 ◽

2020 ◽

Vol 32 (14) ◽

Author(s):

Haibo Wu ◽

Shiliang Shi ◽

Yi Lu ◽

Yong Liu ◽

Weihong Huang

Keyword(s):

Support Vector Regression ◽

Support Vector ◽

Gas Concentration ◽

Regression Algorithms ◽

Concentration Prediction

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PM2.5 concentration prediction based on pseudo-F statistic feature selection algorithm and support vector regression

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/569/1/012039 ◽

2020 ◽

Vol 569 ◽

pp. 012039

Author(s):

Wenbo Liu ◽

Shengnan Liang ◽

Quan Yu

Keyword(s):

Feature Selection ◽

Support Vector Regression ◽

Support Vector ◽

Selection Algorithm ◽

Feature Selection Algorithm ◽

Concentration Prediction ◽

Pm2.5 Concentration

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Predicting the geometry of regime rivers using M5 model tree, multivariate adaptive regression splines and least square support vector regression methods

International Journal of River Basin Management ◽

10.1080/15715124.2018.1546731 ◽

2018 ◽

Vol 17 (3) ◽

pp. 333-352 ◽

Cited By ~ 6

Author(s):

Saba Shaghaghi ◽

Hossein Bonakdari ◽

Azadeh Gholami ◽

Ozgur Kisi ◽

Andrew Binns ◽

...

Keyword(s):

Support Vector Regression ◽

Least Square ◽

Multivariate Adaptive Regression Splines ◽

Support Vector ◽

Regression Splines ◽

M5 Model Tree ◽

Regression Methods ◽

Adaptive Regression ◽

Adaptive Regression Splines ◽

M5 Model

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PREDICTING THE PRICE OF CRYPTOCURRENCY USING SUPPORT VECTOR REGRESSION METHODS

JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES ◽

10.26782/jmcms.2020.04.00023 ◽

2020 ◽

Vol 15 (4) ◽

Author(s):

Saad Ali Alahmari

Keyword(s):

Support Vector Regression ◽

Support Vector ◽

Regression Methods

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