Results 21 to 30 of about 184,733 (266)
Abstract and Applied Analysis, 2014 We introduce a new parametric kernel function, which is a combination of the classic kernel function and a trigonometric barrier term, and present various properties of this new kernel function.
X. Z. Cai +3 more
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Advances in Mechanical Engineering, 2018 Aiming at the problem of gear fault diagnosis, in order to effectively extract the features and improve the accuracy of gear fault diagnosis, the method based on wavelet-packet independent component analysis and support vector machine with kernel ...
Lizheng Pan +5 more
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Breakdown Point of Robust Support Vector Machines
Entropy, 2017 Support vector machine (SVM) is one of the most successful learning methods for solving classification problems. Despite its popularity, SVM has the serious drawback that it is sensitive to outliers in training samples.
Takafumi Kanamori +2 more
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Journal of Hydroinformatics, 2021 Dam deformation monitoring and prediction are crucial for evaluating the safety of reservoirs. There are several elements that influence dam deformation. However, the mixed effects of these elements are not always linear.
Youliang Chen +4 more
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Classification of raw milk composition and somatic cell count in water buffaloes with support vector machines [PDF]
Kafkas Universitesi Veteriner Fakültesi Dergisi, 2020 The study investigates the classification of milk quality with support vector machines (SVM) using the raw milk composition and somatic cell count (SCC) data on buffalos.
Yalcin TAHTALI
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The Cauchy kernel, the Szeg� kernel, and the Riemann mapping function
Mathematische Annalen, 1978 Stein E M, E M Stein
exaly +3 more sources
On the Approximation of Kernel functions
J. Mach. Learn. Res.Various methods in statistical learning build on kernels considered in reproducing kernel Hilbert spaces. In applications, the kernel is often selected based on characteristics of the problem and the data. This kernel is then employed to infer response variables at points, where no explanatory data were observed. The data considered here are located in
Paul Dommel, Alois Pichler
openaire +4 more sources
Alexandria Engineering Journal, 2020 In this paper, on the basis of the reproducing kernel functions, a novel meshless algorithm is explored for fractional advection–diffusion-reaction equations (ADREs) with Caputo time variable order.
Xiuying Li, Boying Wu
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Effects of Memory Dependent Derivative of Bio-heat Model in Skin Tissue exposed to Laser Radiation [PDF]
EAI Endorsed Transactions on Pervasive Health and Technology, 2020 INTRODUCTION: Thermal processes are the essence of living organisms and are necessary for understanding life. The study of Transfer of heat in tissues is known as Bioheat transfer. Many techniques are developed for the thermal treatment of skin and other
Iqbal Kaur, Parveen Lata, K. Handa
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Scientific Reports, 2022 In view of the shortcomings of existing artificial neural network (ANN) and support vector regression (SVR) in the application of three-dimensional displacement back analysis, Gaussian process regression (GPR) algorithm is introduced to make up for the ...
Hanghang Yan +3 more
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