least squares support vector machine
Least Squares Support Vector Machine for Constitutive Modeling of Clay
... and support vector machine (SVM) have been successfully used in constitutive modeling of ...paper, least squares support vector machine (LSSVM) is proposed to ...
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Classification of Clustered Microcalcifications in Mammograms using Particle Swarm Optimization and Least Squares Support Vector Machine
... principle, least-squares support vector machine (LSSVM) [15,16] is similar to standard SVM [14] but the former accomplishes learning task by using least-square empirical error as ...
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A novel fault-tolerant control strategy for near space hypersonic vehicles via least squares support vector machine and backstepping method
... In this paper, the first an attitude observer has been designed for the reentry process of the NSHV by using the LSSVM technique which uses the principle of least squares support vector ...
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Multi-phase classification by a least-squares support vector machine approach in tomography images of geological samples
... Abstract. Image processing of X-ray-computed polychro- matic cone-beam micro-tomography (µXCT) data of geo- logical samples mainly involves artefact reduction and phase segmentation. For the former, the main ...
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Analysis of Ammonia Nitrogen Content in Water Based on Weighted Least Squares Support Vector Machine (WLSSVM) Algorithm
... [4], support vector machine [5] and other forecasting methods can be used to establish data prediction model, but the neural network requires a large number of training sample data, not suitable for ...
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Using Principal Component Analysis and Least Squares Support Vector Machine to Predict the Silicon Content in Blast Furnace System
... and least squares support vector machine (LSSVM) [15-25] model, and constructs a new multivariable combination forecasting model for furnace temperature ...
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Segmentation algorithm for Hangzhou white chrysanthemums based on least squares support vector machine
... Abstract: In order to realize the visual positioning for Hangzhou white chrysanthemums harvesting robot in natural environment, a color image segmentation method for Hangzhou white chrysanthemum based on least ...
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Determination of 137Ba Isotope Abundances in Water Samples by Inductively Coupled Plasma-optical Emission Spectrometry Combined with Least-squares Support Vector Machine Regression
... A simple and rapid method for the determination of 137 Ba isotope abundances in water samples by inductively coupled plasma-optical emission spectrometry (ICP-OES) coupled with least-squares support ...
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← Return to Article Details ENHANCEMENT SPECTRAL RESOLUTION FOR THE PREDICTION AMOUNT OF SOFOSBUVIR AND LEDIPASVIR USING LEAST SQUARES SUPPORT VECTOR MACHINE AND ARTIFICIAL NEURAL NETWORKS IN PHARMACEUTICAL FORMULATION
... The network was formed with 2 and 5 layers and 2, 5, 7, 9 neurons in each layer for SOF and LED. Hyperbolic tangent sigmoid (TANSIG) and a linear (PURELIN) as transfer functions were selected for the first and second ...
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Parsimonious least squares support vector regression using orthogonal forward selection with the generalised kernel model
... learning machine. Forward selection using the Orthogonal Least Squares (OLS) algorithm (Chen et ...the Support Vector Machine (SVM) (Chapelle et ...The Least ...
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ASSOCIATION RULE MINING BASED VIDEO CLASSIFIER WITH LATE ACCEPTANCE HILL CLIMBING APPROACH
... weighted least squares support vector machine algorithm and putting fuzzy weighted membership on the squared error of each sample ...weighted least squares support ...
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A synthetic approach to weathering degree classification of stone relics case study of the Yungang Grottoes
... ultrasonic machine, and the corre- sponding ultrasonic velocities were ...a least squares support vector machine ...a machine learning software package known for its quick ...
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Detection of Retinal Blood Vessels for Disease Prediction using Machine Learning
... 2) “Shishir Maheshwari”, et al [6] introduces an automated diagnosis of glaucoma system. The available scanning methods are Heidelberg Retinal Tomography (HRT), Scanning Laser Polarimetry (SLP) and Optical Coherence ...
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Machine learning prediction Models of Electrical Efficiency of Photovoltaic-Thermal Collectors
... the least pollution impact between the available alternatives of fossil ...investigation, machine leaening approaches of neural networks (NN), neuro-fuzzy and least squares support ...
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Algorithm Model and Performance Evaluation of P2P Network System under the Internet of Things
... First, investigation of a mapping model of packet loss rate and the Quality of experience [1] . Second, Research on Packet loss rate mapped to the Quality of experience [2] . Third, Investigation of the influencing ...
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Hybridizing GMDH and least squares SVM support vector machine for forecasting tourism demand
... handling least squares support vector machine (GLSSVM) algorithm, which combines the theory a group method of data handling (GMDH) with the least squares support ...
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Text Classification Using ES Based L1 LS SVM
... Because the –insensitive loss function used in SVM is replaced by a sum square error loss function, the inequality restriction is replaced by the equation restriction. Thus this makes the least squares ...
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Diabetic Retinopathy, an Eye Disease Prediction System: Survey
... 2) “Shishir Maheshwari”, et al [6] introduces an automated diagnosis of glaucoma system. The available scanning methods are Heidelberg Retinal Tomography (HRT), Scanning Laser Polarimetry (SLP) and Optical Coherence ...
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Earlier Detection of Glaucoma using Empirical Wavelet Transform
... Abstract: Glaucoma is an ocular disorder caused due to increased fluid pressure in the optic nerve. It damages the optic nerve subsequently causes loss of vision. The available scanning methods are Heidelberg Retinal ...
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The Improved Least Square Support Vector Machine Based on Wolf Pack Algorithm and Data Inconsistency Rate for Cost Prediction of Substation Projects
... improved least squares support vector machine (ILSSVM) optimized by wolf pack algorithm(WPA) is proposed to improve the accuracy and stability of the cost forecasting of substation ...
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