Results 11 to 20 of about 176,617 (264)
Frontiers in Pharmacology, 2023 The target of the study is to predict the inhibitory effect of amide derivatives on xanthine oxidase (XO) by building several models, which are based on the theory of the quantitative structure–activity relationship (QSAR).
Xiaoda Yang +3 more
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New Mixed Kernel Functions of SVM Used in Pattern Recognition
Cybernetics and Information Technologies, 2016 The pattern analysis technology based on kernel methods is a new technology, which combines good performance and strict theory. With support vector machine, pattern analysis is easy and fast. But the existing kernel function fits the requirement.
Huanrui Hao
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Genome-Wide Gene-Based Multi-Trait Analysis
Frontiers in Genetics, 2020 Genome-wide association studies focusing on a single phenotype have been broadly conducted to identify genetic variants associated with a complex disease.
Yamin Deng +5 more
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Energies, 2022 The calorific value of coal gangue is a critical index for coal waste recycling and the energy industry. To establish an accurate and efficient calorific value forecasting model, a method based on hybrid kernel function–support vector regression and ...
Xiangbing Gao +3 more
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A Theorem for Kernel Functions [PDF]
Proceedings of the American Mathematical Society, 1951 Let B be a domain lying in the complex z plane and KB(Z, i) its kernel function. A number of relationships exist between the kernel and the geometric properties of the domain. (See, for example, [I'].)i It is the purpose of the-present note to relate the successive derivatives of the kernel with the domain B.
Davis, Philip, Pollak, Henry
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Journal of Control Science and Engineering, 2017 Support vector regression algorithm is widely used in fault diagnosis of rolling bearing. A new model parameter selection method for support vector regression based on adaptive fusion of the mixed kernel function is proposed in this paper.
Hailun Wang, Daxing Xu
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Introducing chaos behavior to kernel relevance vector machine (RVM) for four-class EEG classification. [PDF]
PLoS ONE, 2018 This paper addresses a chaos kernel function for the relevance vector machine (RVM) in EEG signal classification, which is an important component of Brain-Computer Interface (BCI).
Enzeng Dong +5 more
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Computing the Wave-Kernel Matrix Functions [PDF]
SIAM Journal on Scientific Computing, 2018 We derive an algorithm for computing the wave-kernel functions cosh \surd A and sinhc\surd A for an arbitrary square matrix A, where sinhcz = sinh(z)/z. The algorithm is based on Pad\'e approximation and the use of double angle formulas. We show that the backward error of any approximation to cosh \surd A can be explicitly expressed in terms of a ...
Nadukandi, Prashanth +1 more
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THE BERGMAN KERNEL FUNCTION AND THE SZEGO KERNEL FUNCTION [PDF]
Journal of the Korean Mathematical Society, 2006 We compute the holomorphic derivative of the harmonic measure associated to a bounded domain in the plane and show that the exact Bergman kernel function associated to a bounded domain in the plane relates the derivatives of the Ahlfors map and the Szego kernel in an explicit way.
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Discrete Dynamics in Nature and Society, 2016 According to the characteristics that the kernel function of extreme learning machine (ELM) and its performance have a strong correlation, a novel extreme learning machine based on a generalized triangle Hermitian kernel function was proposed in this ...
Senyue Zhang, Wenan Tan
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