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Results 1 to 25 of 1917

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Support vector regression methodology for wind turbine reaction torque prediction with power-split hydrostatic continuous variable transmissionSHAMSHIRBAND, Shahaboddin; PETKOVIC, Dalibor; AMINI, Amineh et al.Energy (Oxford). 2014, Vol 67, pp 623-630, issn 0360-5442, 8 p.Article

Auto-weighted support vector machines for training sets with multi-duplicate samplesJIA YINSHAN; JIA CHUANYING; MA HENG et al.International Conference on Signal Processing. 2004, pp 1447-1450, isbn 0-7803-8406-7, 4 p.Conference Paper

Method for restoring PPG signals using ECG correspondences and SVRKIM, H; KIM, Y; KIM, J et al.Electronics letters. 2013, Vol 49, Num 24, pp 1518-1520, issn 0013-5194, 3 p.Article

Multiclass classification machine based on the analytical centerXIANGQIAN LI; JIANHAI YUE; YONGGANG LENG et al.International Conference on Signal Processing. 2004, pp 1471-1474, isbn 0-7803-8406-7, 4 p.Conference Paper

Using membership functions to improve multi-class SVM classificationWANG, Xiaodan; WU, Chongming.International Conference on Signal Processing. 2004, pp 1459-1462, isbn 0-7803-8406-7, 4 p.Conference Paper

What is a support vector machine?NOBLE, William S.Nature biotechnology. 2006, Vol 24, Num 12, pp 1565-1567, issn 1087-0156, 3 p.Article

Computational estimation of nano-photocatalyst activity : Feasibility of kernel based learning machinesSTRAUSS, Daniel J; SCHÄFER, Gerd; AKARSU, Murat et al.IEEE conference on nanotechnology. 2004, pp 443-445, isbn 0-7803-8536-5, 1Vol, 3 p.Conference Paper

Bi-model short-term solar irradiance prediction using support vector regressorsCHENG, Hsu-Yung; YU, Chih-Chang; LIN, Sian-Jing et al.Energy (Oxford). 2014, Vol 70, pp 121-127, issn 0360-5442, 7 p.Article

An improved cluster labeling method for support vector clusteringLEE, Jaewook; LEE, Daewon.IEEE transactions on pattern analysis and machine intelligence. 2005, Vol 27, Num 3, pp 461-464, issn 0162-8828, 4 p.Article

Prediction of maize single-cross hybrid performance: support vector machine regression versus best linear predictionMAENHOUT, Steven; DE BAETS, Bernard; HAESAERT, Geert et al.Theoretical and applied genetics. 2010, Vol 120, Num 2, pp 415-427, issn 0040-5752, 13 p.Conference Paper

Machine Learning in Speech and Language TechnologiesFUNG, Pascale; ROTH, Dan.Machine learning. 2005, Vol 60, Num 1-3, issn 0885-6125, 278 p.Serial Issue

A new PU learning algorithm for test classificationHAILONG YU; WANLI ZUO; TAO PENG et al.Lecture notes in computer science. 2005, pp 824-832, issn 0302-9743, isbn 3-540-29896-7, 1Vol, 9 p.Conference Paper

Multidimensional svm to include the samples of the derivatives in the reconstruction of a functionPEREZ-CRUZ, Fernando; LAZARO, Marcelino; ARTES-RODRIGUEZ, Antonio et al.EUSIPCO. Conference. 2004, isbn 3-200-00148-8, 3Vol, volI, 597-600Conference Paper

Assessing the Freshness of Meat by Using Quantum-Behaved Particle Swarm Optimization and Support Vector MachineXIAO GUAN; JING LIU; QINGRONG HUANG et al.Journal of food protection. 2013, Vol 76, Num 11, pp 1916-1922, issn 0362-028X, 7 p.Article

Support vector machines regression and modeling of greenhouse environmentDINGCHENG WANG; MAOHUA WANG; XIAOJUN QIAO et al.Computers and electronics in agriculture. 2009, Vol 66, Num 1, pp 46-52, issn 0168-1699, 7 p.Article

Application des noyaux multiples de type Kernel Basis à la méthode Relevance Vector Machine pour la sélection de modèles = Application of multiple kernels like Kernel Basis to the Relevance Vector Machine method for model selectionSUARD, Frédéric; MERCIER, David.Colloque sur le traitement du signal et des images. 2009, 1Vol, p. 137Conference Paper

Increasing the discrimination power of the co-occurrence matrix-based featuresGELZINIS, A; VERIKAS, A; BACAUSKIENE, M et al.Pattern recognition. 2007, Vol 40, Num 9, pp 2367-2372, issn 0031-3203, 6 p.Article

Improving RTDGPS accuracy using hybrid PSOSVM prediction modelMOHAMAD HOSEIN REFAN; DAMESHGHI, Adel; KAMARZARRIN, Mehrnoosh et al.Aerospace science and technology (Imprimé). 2014, Vol 37, pp 55-69, issn 1270-9638, 15 p.Article

Support Vector Machines in Remote Sensing: The Tricks of the TradeCAMPS-VALLS, Gustavo.Proceedings of SPIE, the International Society for Optical Engineering. 2011, Vol 8180, issn 0277-786X, isbn 978-0-8194-8807-7, 81800B.1-81800B.9Conference Paper

Predicting post-translational lysine acetylation using support vector machinesGNAD, Florian; SHUBIN REN; CHOUDHARY, Chunaram et al.Bioinformatics (Oxford. Print). 2010, Vol 26, Num 13, pp 1666-1668, issn 1367-4803, 3 p.Article

Application of distributed SVM architectures in classifying forest data cover typesTREBAR, Mira; STEELE, Nigel.Computers and electronics in agriculture. 2008, Vol 63, Num 2, pp 119-130, issn 0168-1699, 12 p.Article

Machines à noyaux pour l'apprentissage statistique = Kernel machines for statistical learningCANU, Stéphane.Techniques de l'ingénieur. Télécoms. 2007, Vol TEB2, Num TE5255, issn 1632-3823, TE5255.1-TE5522.20Article

Applications of neural networksSMITH, Kate A.Computers & operations research. 2005, Vol 32, Num 10, issn 0305-0548, 237 p.Serial Issue

Least squares littlewood-paley wavelet support vector machineFANGFANG WU; YINLIANG ZHAO.Lecture notes in computer science. 2005, pp 462-472, issn 0302-9743, isbn 3-540-29896-7, 1Vol, 11 p.Conference Paper

Research on methodology of document classification based on generalized learningYAO, Min; JIANG, Zhiwei; JING, Xiaogan et al.Proceedings of SPIE, the International Society for Optical Engineering. 2005, pp 60432E.1-60432E.7, issn 0277-786X, isbn 0-8194-6075-3, 2VolConference Paper

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