Modeling the magnetocaloric effect of manganite using hybrid genetic and support vector regression algorithms

2019 ◽  
Vol 383 (15) ◽  
pp. 1782-1790 ◽  
Author(s):  
Taoreed O. Owolabi
Keyword(s):  
Support Vector Regression ◽  
Magnetocaloric Effect ◽  
Support Vector ◽  
Regression Algorithms

Prediction of hourly O3 concentrations using support vector regression algorithms

2010 ◽  
Vol 44 (35) ◽  
pp. 4481-4488 ◽  
Author(s):  
E.G. Ortiz-García ◽  
S. Salcedo-Sanz ◽  
Á.M. Pérez-Bellido ◽  
J.A. Portilla-Figueras ◽  
L. Prieto
Keyword(s):  
Support Vector Regression ◽  
Support Vector ◽  
Regression Algorithms

scholarly journals Efficient prediction of total column ozone based on support vector regression algorithms, numerical models and Suomi-satellite data

Atmósfera ◽  
2017 ◽  
Vol 30 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Leo Carro-Calvo ◽  
◽  
Carlos Casanova-Mateo ◽  
Julia Sanz-Justo ◽  
José Luis Casanova-Roque ◽  
...  
Keyword(s):  
Support Vector Regression ◽  
Satellite Data ◽  
Numerical Models ◽  
Support Vector ◽  
Total Column Ozone ◽  
Regression Algorithms ◽  
Efficient Prediction ◽  
Column Ozone ◽  
Total Column

Characterization and Modeling of Corn Stalk Fibers tied with Clay using Support Vector Regression Algorithms

2021 ◽  
pp. 1-16
Author(s):  
Giuseppe Ciaburro ◽  
Virginia Puyana-Romero ◽  
Gino Iannace ◽  
Wilson Andres Jaramillo-Cevallos
Keyword(s):  
Support Vector Regression ◽  
Support Vector ◽  
Corn Stalk ◽  
Regression Algorithms

scholarly journals Computational prediction model for pepper yield prediction using support vector regression.

2021 ◽  
Author(s):  
Akhil Wilson ◽  
N. Hemalatha ◽  
Raji Sukumar
Keyword(s):  
Machine Learning ◽  
Support Vector Regression ◽  
Climatic Condition ◽  
Research Work ◽  
Computational Prediction ◽  
Support Vector ◽  
Yield Prediction ◽  
Challenging Problem ◽  
Regression Algorithms ◽  
The One

Abstract The yield prediction is the one of the challenging problem in agriculture. Here in this research work we have predicted the yield of Pepper in the state of Kerala, India. With the help of Machine Learning and by considering the soil properties, micro climatic condition and area of the Pepper we have predicted the yield. Here we have used Linear Regression and Support Vector Regression algorithms in order to predict the pepper yield. Experimental results gave best accuracy of 97.685% for Support Vector Regression.

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