Search Results - Support vector regression algorithms

Predicting Microbial Populations in Seafood using Support Vector Regression Algorithms and Electronic Nose

Authors: Emung Zakaria Dedy Rahman Wijaya Tedi Gunawan

Source: 2023 International Conference on Artificial Intelligence Robotics, Signal and Image Processing (AIRoSIP). :280-284

Linear Programming Twin Support Vector Regression

Authors: Tanveer, M.

Source: Filomat, 2017 Jan 01. 31(7), 2123-2142.

Access URL: https://www.jstor.org/stable/26194949

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

Authors: Giuseppe Ciaburro Virginia Puyana-Romero Gino Iannace et al.

Source: Journal of Natural Fibers, Vol 19, Iss 13, Pp 7141-7156 (2022)

Subject Terms: 天然材料, 向量机回归模型, Science, TP890-933, 0103 physical sciences, 声学测量, Textile bleaching, dyeing, printing, etc, 01 natural sciences, Natural materials, sound absorption coefficient, vector machine regression model, acoustic measurements, 吸声系数, 12. Responsible consumption

Access URL: https://doaj.org/article/5f9e7e392f2742a3b95ae6b14745208e

Comparison of Triple Exponential Smoothing and Support Vector Regression Algorithms in Predicting Drug Usage at Puskesmas

Authors: Syafira Agnesti Alwis Nazir Iwan Iskandar et al.

Source: Sistemasi: Jurnal Sistem Informasi, Vol 12, Iss 3, Pp 996-1006 (2023)

Subject Terms: Technology, Information technology, T58.5-58.64

File Description: electronic resource

Relation: http://sistemasi.ftik.unisi.ac.id/index.php/stmsi/article/view/3499; https://doaj.org/toc/2302-8149; https://doaj.org/toc/2540-9719

Access URL: https://doaj.org/article/23d8a9f607d94d8bb706d9ec9db59f85

Quantitative analysis of Elastic Optical Networks using Probabilistic and Support Vector Regression Algorithms

Authors: A. Akilandeswari D. Sungeetha Himanshu Shekhar et al.

Source: 2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC). :1434-1440

Comparison of Bayesian Regularized Neural Network, Random Forest Regression, Support Vector Regression and Multivariate Adaptive Regression Splines Algorithms to Predict Body Weight from Biometrical Measurements in Thalli Sheep.

Alternate Title: Thalli Koyunlarında Biyometrik Ölçümlerden Vücut Ağırlığı Tahmini İçin Bayesian Regularized Neural Network, Random Forest Regresyon, Support Vector Regresyon ve Çok Değişkenli Regresyon Uzanımları Algoritmalarının Karşılaştırılması

Authors: TIRINK, Cem¹ cem.tirink@gmail.com

Source: Kafkas Üniversitesi Veteriner Fakültesi Dergisi. May/Jun2022, Vol. 28 Issue 3, p411-419. 9p.

Subjects: Random forest algorithms, Body weight, Splines, Sheep breeds, Sheep, Ear, Artificial neural networks

Improving accuracy in screen time prediction using decision tree algorithm compared with support vector regression algorithm.

Authors: Saathwik, B. Ramachandran, A. G.

Source: AIP Conference Proceedings; 2025, Vol. 3300 Issue 1, p1-10, 10p

Subject Terms: DECISION trees, SCREEN time, MACHINE learning, DATA analysis, STATISTICAL significance, REGRESSION analysis, ALGORITHMS, STATISTICAL accuracy

Penerapan Algoritma Linear Regression dan Support Vector Regression dalam Prediksi Temperatur Udara di Malang. (Indonesian)

Alternate Title: Application of Linear Regression and Support Vector Regression Algorithms in Air Temperature Prediction in Malang. (English)

Authors: Karnisih Sunarno Iqbal et al.

Source: Techno.com; Feb2025, Vol. 24 Issue 1, p218-229, 12p

Subject Terms: MACHINE learning, ATMOSPHERIC temperature, DEW point, CLIMATE change, SOLAR radiation

Rainfall Prediction Using Logistic Regression and Support Vector Regression Algorithms

Authors: Srikantaiah K. C Meenaxi M. Sanadi

Source: Communications in Computer and Information Science ISBN: 9783030814618

Subject Terms: 13. Climate action

Access URL: https://link.springer.com/chapter/10.1007/978-3-030-81462-5_54
https://rd.springer.com/chapter/10.1007/978-3-030-81462-5_54

Machine Learning Techniques For Stock Price Prediction - A Comparative Analysis Of Linear Regression, Random Forest, And Support Vector Regression.

Authors: Pashankar, Shital Sameer Shendage, Jyoti Dashrath Pawar, Janardan

Source: Journal of Advanced Zoology. 2024 Supplement, Vol. 45, p118-127. 10p.

Prediction of global solar irradiation using hybridized k-means and support vector regression algorithms

Authors: Temitope Raphael Ayodele Josiah L. Munda A. Amedu et al.

Source: Renewable Energy Focus. 29:78-93

Subject Terms: 13. Climate action, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 7. Clean energy

Access URL: https://www.sciencedirect.com/science/article/pii/S1755008418304022

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

Authors: Taoreed O. Owolabi

Source: Physics Letters A. 383:1782-1790

Subject Terms: 0103 physical sciences, 02 engineering and technology, 0210 nano-technology, 01 natural sciences, 7. Clean energy

Access URL: https://www.sciencedirect.com/science/article/pii/S0375960119301835
http://ui.adsabs.harvard.edu/abs/2019PhLA..383.1782O/abstract

Estimation of a novel artificial neural networks over support vector regression to improve accuracy in flood prediction.

Authors: Basha, M. Hussain Priyadarsini, P. S. Uma

Source: AIP Conference Proceedings; 2025, Vol. 3252 Issue 1, p1-7, 7p

Subject Terms: ARTIFICIAL neural networks, SUPPORT vector machines, FLOOD forecasting, STATISTICAL significance, ALGORITHMS

Flood Susceptibility Assessment Using Novel Ensemble of Hyperpipes and Support Vector Regression Algorithms

Authors: Asish Saha Subodh Pal Alireza Arabameri et al.

Contributors: Asish Saha Subodh Pal Alireza Arabameri et al.

Source: Water
Volume 13
Issue 2

Subject Terms: hyperpipes (HP), support vector regression (SVR), ensemble approach, 13. Climate action, 1. No poverty, Support vector regression (SVR), Flood susceptibility assessment, 15. Life on land, flood susceptibility assessment, Hyperpipes (HP), 6. Clean water, Ensemble approach, Koiya River basin

File Description: application/pdf

Access URL: https://www.mdpi.com/2073-4441/13/2/241/pdf
https://www.mdpi.com/2073-4441/13/2/241/pdf
https://www.mdpi.com/2073-4441/13/2/241
https://resolver.obvsg.at/urn:nbn:at:at-ubs:3-26684
https://eplus.uni-salzburg.at/id/7950780
https://doi.org/10.3390/w13020241

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

Authors: José Luis Casanova-Roque Sancho Salcedo-Sanz Leo Carro-Calvo et al.

Source: Atmósfera. 30:1-10

Subject Terms: 13. Climate action, 14. Life underwater, 16. Peace & justice, 7. Clean energy, 01 natural sciences, 0105 earth and related environmental sciences

Access URL: https://www.revistascca.unam.mx/atm/index.php/atm/article/download/ATM.2017.30.01.01/46580
https://www.revistascca.unam.mx/atm/index.php/atm/article/view/ATM.2017.30.01.01
https://www2.revistascca.unam.mx/atm/index.php/atm/article/view/atm.2017.30.01.01/0
https://www.sciencedirect.com/science/article/pii/S0187623617300371
https://www2.revistascca.unam.mx/atm/index.php/atm/article/download/ATM.2017.30.01.01/46580
https://www.revistascca.unam.mx/atm/index.php/atm/article/download/ATM.2017.30.01.01/46580
https://www.elsevier.es/es-revista-atmosfera-76-articulo-efficient-prediction-total-column-ozone-S0187623617300371

Projection support vector regression algorithms for data regression

Authors: Dong Xu Xinjun Peng

Source: Knowledge-Based Systems. 112:54-66

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://dblp.uni-trier.de/db/journals/kbs/kbs112.html#PengX16
https://www.sciencedirect.com/science/article/pii/S0950705116303070

Türkiye’deki il yolları için Yıllık Ortalama Günlük Trafik (YOGT) tahmininde makine öğrenmesi algoritmalarının karşılaştırmalı analizi. (Turkish)

Alternate Title: A comparative analysis of machine learning algorithms for estimating Annual Average Daily Traffic (AADT) on provincial roads in Turkey. (English)

Authors: Biçici, Serkan

Source: Nigde Omer Halisdemir University Journal of Engineering Sciences / Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi; 2025, Vol. 14 Issue 4, p1612-1624, 13p

Subject Terms: RANDOM forest algorithms, TRAFFIC estimation, MACHINE learning, SUPPORT vector machines, TRAFFIC flow, SOCIODEMOGRAPHIC factors, ROADS

Geographic Terms: TURKEY

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

Authors: Haibo Wu Shiliang Shi Yi Lu et al.

Source: Concurrency and Computation: Practice and Experience. 32

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 7. Clean energy

Access URL: https://onlinelibrary.wiley.com/doi/full/10.1002/cpe.5705
https://dblp.uni-trier.de/db/journals/concurrency/concurrency32.html#WuSLLH20

Accurate estimation of significant wave height with Support Vector Regression algorithms and marine radar images

Authors: Sancho Salcedo-Sanz Enrique Alexandre Laura Cornejo-Bueno et al.

Source: Coastal Engineering. 114:233-243

Subject Terms: 0211 other engineering and technologies, 02 engineering and technology, 14. Life underwater, 01 natural sciences, 0105 earth and related environmental sciences

Access URL: https://www.sciencedirect.com/science/article/pii/S0378383916300412
http://www.sciencedirect.com/science/article/pii/S0378383916300412

Quantitative prediction of hERG inhibitory activities using support vector regression and the integrated hERG dataset in AMED cardiotoxicity database

Authors: Hitomi Yuki Teruki Honma Tomohiro Sato

Source: Chem-Bio Informatics Journal. 2021, 21:70