Improving Harris hawks optimization algorithm for hyperparameters estimation and feature selection in v‐support vector regression based on opposition‐based learning
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Chemometrics"
DOI: 10.1002/cem.3311
Abstract: Many real problems have been solved by support vector regression, especially v‐support vector regression (v‐SVR), but there are hyperparameters that usually needed to tune. In addition, v‐SVR cannot perform feature selection. Nature‐inspired algorithms have been… read more here.
Keywords: vector regression; feature; feature selection; support vector ... See more keywords
Intelligent optimization of bioleaching process for waste lithium‐ion batteries: An application of support vector regression approach
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Energy Research"
DOI: 10.1002/er.6238
Abstract: Recovery of toxic and vital metal from spent Li‐ion batteries is a vital problem in the recycling industry. The recycling processes such as bioleaching are much simpler and environment friendly but lack the required efficiency… read more here.
Keywords: bioleaching process; recovery; ion batteries; vector regression ... See more keywords
Classify patients with Moyamoya disease according to their cognitive performance might be helpful in clinical and practical with support vector machine based on hypergraph
Sign Up to like & getrecommendations! Published in 2023 at "Human Brain Mapping"
DOI: 10.1002/hbm.26218
Abstract: Moyamoya disease (MMD) patients were now classified according to their cerebrovascular manifestations, with cognition and emotion ignored, which attenuated the therapy. The present study tried to classify them based on their cognitive and emotional performance… read more here.
Keywords: vector machine; support vector; moyamoya disease; mmd ... See more keywords
Liver tissue classification of en face images by fractal dimension-based support vector machine.
Sign Up to like & getrecommendations! Published in 2020 at "Journal of biophotonics"
DOI: 10.1002/jbio.201960154
Abstract: Full-field optical coherence tomography (FF-OCT) has been reported with its label-free subcellular imaging performance. To realize quantitive cancer detection, the support vector machine (SVM) model of classifying normal and cancerous human liver tissue is proposed… read more here.
Keywords: liver tissue; support vector; tissue; fractal dimension ... See more keywords
Brain tumor classification of virtual NMR voxels based on realistic blood vessel-induced spin dephasing using support vector machines.
Sign Up to like & getrecommendations! Published in 2020 at "NMR in biomedicine"
DOI: 10.1002/nbm.4307
Abstract: Remodeling of tissue microvasculature commonly promotes neoplastic growth; however, there is no imaging modality in oncology yet that noninvasively quantifies microvascular changes in clinical routine. Although blood capillaries cannot be resolved in typical magnetic resonance… read more here.
Keywords: nmr voxels; classification; support vector; vector machines ... See more keywords
Multi‐innovation Newton recursive methods for solving the support vector machine regression problems
Sign Up to like & getrecommendations! Published in 2021 at "International Journal of Robust and Nonlinear Control"
DOI: 10.1002/rnc.5672
Abstract: The support vector machine has been widely used in binary classification applications because of the simplicity of its implementation. This article proposes an online identification method based on the support vector machine in the field… read more here.
Keywords: vector; vector machine; support vector; newton recursive ... See more keywords
Parallel Clifford Support Vector Machines Using the Gaussian Kernel
Sign Up to like & getrecommendations! Published in 2017 at "Advances in Applied Clifford Algebras"
DOI: 10.1007/s00006-016-0726-2
Abstract: This work presents a parallelization method for the Clifford support vector machines, based in two characteristics of the Gaussian Kernel. The pure real-valued result and its commutativity allows us to separate the multivector data in… read more here.
Keywords: vector machines; gaussian kernel; clifford support; support vector ... See more keywords
Developing a least squares support vector machine for estimating the blast-induced flyrock
Sign Up to like & getrecommendations! Published in 2017 at "Engineering with Computers"
DOI: 10.1007/s00366-017-0568-0
Abstract: In blasting operations, the main purpose is to provide appropriate rock fragmentation and to avoid adverse effects such as flyrock and vibration. This paper presents the applicability of least squares support vector machines (LS-SVM) for… read more here.
Keywords: induced flyrock; blast induced; least squares; support vector ... See more keywords
Solving the stochastic support vector regression with probabilistic constraints by a high-performance neural network model
Sign Up to like & getrecommendations! Published in 2021 at "Engineering With Computers"
DOI: 10.1007/s00366-020-01214-5
Abstract: This paper offers a recurrent neural network to support vector machine (SVM) learning in stochastic support vector regression with probabilistic constraints. The SVM is first converted into an equivalent quadratic programming (QP) formulation in linear… read more here.
Keywords: neural network; network; support vector; stochastic support ... See more keywords
A new branch-and-bound approach to semi-supervised support vector machine
Sign Up to like & getrecommendations! Published in 2017 at "Soft Computing"
DOI: 10.1007/s00500-016-2089-y
Abstract: This paper develops a branch-and-bound algorithm to solve the 2-norm soft margin semi-supervised support vector machine. First, the original problem is reformulated as a non-convex quadratically constrained quadratic programming problem with a simple structure. Then,… read more here.
Keywords: support vector; semi supervised; supervised support; vector machine ... See more keywords
Clustering via fuzzy one-class quadratic surface support vector machine
Sign Up to like & getrecommendations! Published in 2017 at "Soft Computing"
DOI: 10.1007/s00500-016-2462-x
Abstract: This paper proposes a soft clustering algorithm based on a fuzzy one-class kernel-free quadratic surface support vector machine model. One main advantage of our new model is that it directly uses a quadratic function for… read more here.
Keywords: support vector; class; fuzzy one; quadratic surface ... See more keywords