least squares support vector machines
Price predictive analysis mechanism utilizing grey wolf optimizer least squares support vector machines
... of Least Squares Support Vector Machines (LSSVM) hyper-parameters' value is crucial in order to obtain a promising generalization on the unseen ...
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The Corporate Financial Forecasting Based on Least Squares Support Vector Machines Methods
... on least squares support vector ...entirely least squares support vector machines methods to build financial fo- recasting models, and to distinguish ...
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Performance evaluation for engineering project management of particle swarm optimization based on least squares support vector machines
... of least squares support vector machines (LSSVM), this paper proposes a new classified model which combines adaptive particle swarm optimization (APSO) algorithm with ...
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River flow time series using least squares support vector machines
... Least squares support vector machines (LSSVM), as a modification of SVM was introduced by Suykens and Van- dewalle ...the least squares linear system as its loss function, ...
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Using Least Squares Support Vector Machines for Frequency Estimation
... A Support Vector Machine (SVM) [8] uses training data as an integral element of the function estimation model as opposed to simply using training data to esti- mate parameters of an a priori model using ...
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Time Series Forecasting Using Wavelet Least Squares Support Vector Machines and Wavelet Regression Models for Monthly Stream Flow Data
... The new method based on the WLSSVM is developed by combining the discrete wavelet transforms (DWT) and least square support vector machines (LSSVM) model for forecasting streamflows. The ...
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Approximate LS-SVM, Container through- -put forecasting, Time series analysis
... Information concerning container throughput is important for container terminal operators in Hong Kong in making operational strategies and investment plans. This paper has proposed a method, called Approximate ...
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Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters
... of least-squares support vector machines, using model selection procedures with, and without, Bayesian regularisation, (LS-SVM and LS-SVM-BR respectively) over the suite of thirteen ...
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Comparative analysis of river flow modelling by using supervised learning technique
... However, the standard SVM is solved using complicated quadratic programming methods, which are often time consuming and has higher computational burden because of the required constrained optimization programming. As a ...
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Classification of Clustered Microcalcifications in Mammograms using Particle Swarm Optimization and Least Squares Support Vector Machine
... The shape feature extraction stage is followed by a heuristic parameter selection stage based on PSO in which feature selection, dimensionally reduction, and LSSVM parameter optimization are accomplished. The outcome of ...
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MODELING AND SIMULATION OF GRID CONNECTED PHOTOVOLTAIC DISTRIBUTED GENERATION SYSTEM
... less support vector ,which lead to a shorter training time, because in calculation we have fully taken into account that constraints produced by non - support vector have effects on target ...
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Quantitative Structure Property Relationships Study of Mobility of Some Benzoaromatic Carboxylate Derivatives by Partial Least Squares and Least-Square Support Vector Machine
... A quantitative structure-property relationship (QSPR) study is suggested for the prediction of mobilities (m) of benzoaromatic carboxylates. Ab initio theory was used to calculate some quantum chemical descriptors ...
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Application of LSSVM to logistics demand forecasting based on grey relational analysis and kernel principal component analysis
... a least squares support vector machines (LSSVM) model based on grey relational analysis (GRA) and kernel principal component analysis (KPCA) for forecasting logistics ...
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Forecast of fund volatility using least squares wavelet support vector regression machines
... Least squares support vector machines (LS-SVM), developed by Suykens and Vandevalle, is an improved type of SVM ...LS-SVM, Least squares support vector ...
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Segmentation algorithm for Hangzhou white chrysanthemums based on least squares support vector machine
... on Support Vector Machines for identifying plants with green spectral components masked and unmasked, the method was also valid for post-treatment evaluation, where loss of greenness in weeds was ...
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Quantitative Analysis of Near-Infrared Spectra by Wavelet-based Interferences Removal and Least Squares Support Vector Regression
... from support vector machines regression (SVR) [29], has been introduced to perform multivariate regression. Instead of the quadratic programming, LS-SVR only requires solving a set of linear ...
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Least Squares Support Vector Machine for Constitutive Modeling of Clay
... learning machines such as artificial neural network (ANN) [1-5] and support vector machine (SVM) [6], are proposed as more effective approaches to represent complex and nonlinear constitutive ...
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An Error Controlled Method to Determine the Stellar Density Function in a Region of the Sky
... the least squares solutions vector, the average square distance between the exact and the least-squares solutions, finally the variance of the density stellar function due to the ...
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A Novel Approach to Design the Intelligent Technique for Intrusion Detection In Cloud
... Abstract— In the cloud computing, security mechanisms are not mature enough to protect the data stored in the cloud. Hence, it is necessary to propose efficient methods for providing security to the data stored in the ...
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Multi-phase classification by a least-squares support vector machine approach in tomography images of geological samples
... a least- squares term to the cost function, which transformed the problem from solving a QP problem to the practically more convenient solving of a set of linear ...
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