Least square support vector regression
Comparison of artificial neural network and coupled simulated annealing based least square support vector regression models for prediction of compressive strength of high-performance concrete
... based least square support vector regression model Support vector machine proposed by Vapnik [23] is a powerful supervised learning method used for nonlinear classication, ...
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A strategy for forecasting option price using fuzzy time series and least square support vector regression with a bootstrap model
... a Least Square Support Vector Regression (LSSVR), and a bootstrap ...Mean Square Error (RMSE), the Mean Absolute Error (MAE) and the correlation coecient (r) of actual and ...
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Daily Discharge Forecasting Using Least Square Support Vector Regression and Regression Tree
... Abstract. Prediction of river ow is one of the main issues in the eld of water resources management. Because of the complexity of the rainfall-runo process, data-driven methods have gained increased importance. In the ...
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Particle swarm optimized partial least square support vector regression model for tax revenue prediction
... of support vector regression(SVR) construct the optimal regression function through risk minimization principle to transform the problem into solving a convex quadratic programming ...data ...
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The Application of Least Square Support Vector Machine as a Mathematical Algorithm for Diagnosing Drilling Effectivity in Shaly Formations
... robust support vector regression (SVR) methodology that offers superior performance for important drilling engineering ...hybrid least square support vector ...
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Development Of An Adaptive Soft Sensor Based On FCMILSSVR
... of Least Square Support Vector Regression (LSSVR) with Fuzzy C-Means (FCM) clustering is proposed in this ...online Support Vector Regression (SVR) ...
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Runway Incursion Event Forecast Model based on LS-SVR with Multi-kernel
... machine, support vector machine (SVM) has been gaining popularity due to their promising performance, such as dealing with the data of small sample, the high dimension and the excellent generalization ...
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Drought forecasting in eastern Australia using multivariate adaptive regression spline, least square support vector machine and M5Tree model
... Drought forecasting based on SPI and data-driven models where drought indicators are used for forecasting, has been researched attentively in different geographic locations. Cancelliere et al. (2007) designed an ...
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Least Square Regression Learning with Data Dependent Hypothesis and Coefficient Regularzation
... where Ω ( ) α is a positive function on ℜ m . Formulation (3) is a data dependent scheme which has been found many applications in the design of support vector machines, micro-array analysis and variable ...
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A hybrid model of self organizing maps and least square support vector machine for river flow forecasting
... the least squares support vector machines ...and regression problems (Han- bay, 2009; Kang et ...the least squares linear system as its loss function, which is computationally ...
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A Hybrid Method of Least Square Support Vector Machine and Bacterial Foraging Optimization Algorithm for Medium Term Electricity Price Forecasting
... as regression models [7], generalized least squares model with auto-correlated residuals [8] and Autoregressive Moving Average Exogenous (ARMAX) model ...
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Parsimonious least squares support vector regression using orthogonal forward selection with the generalised kernel model
... centre vector and diagonal covariance ...Mean Square Eerror ...centre vector and diagonal covariance matrix is performed using a guided random search algorithm called the Repeated Weighted Boosting ...
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Modeling of Corrosion-Fatigue Crack Growth Rate Based on Least Square Support Vector Machine Technique
... radial basis function network and genetic algorithms to optimize the back propagation network for the fatigue crack growth calculations. The results indicate that the applied model can successfully predict the ...
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Hybrid Simulation of a Frame Equipped with MR Damper by Utilizing Least Square Support Vector Machine
... 2. Least square support vector machine (LS-SVM) Supervised learning systems that analyze data and recognize patterns, known as support vector machines (SVMs), are used for ...
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Self organizing map and least square support vector machine method for river flow modelling
... called Least Square Support Vector Machine (LSSVM) to encounter the SVM quadratic programming ...the least squares linear system as its loss function, which is computationally ...and ...
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Aircraft taxi time prediction: comparisons and insights
... erent regression approaches for Zurich ...linear regression approach (LinReg) which is used as a baseline ...that least median square linear regression performs (LMS) poorly for ...
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Study On Prediction Models For Integrated Scheduling In Semiconductor Manufacturing Lines
... Extreme Least Square Support Vector Machine for quality prediction and integrated scheduling of semiconductor production line is presented, in which data is first mapped into ELM feature space ...
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Diabetes Prediction using Linear Regression, Decision Tree & Least Square Support Vector Machine
... Confusion Matrix pertaining set of predictors among which some are significant in terms of mean and variance than others where estimating the predictors if the same significant predictors before prediction, pose as ...
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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
... the least squares support vector machines ...mean square error of prediction (RMSEP) of ...linear regression (MLR) and partial least squares ...
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Multi-Output Least Square Support Vector Machine for the Reconstruction of Perfect Electric Conductor Below Rough Surface
... a regression problem and solves it using learning by examples ...application. Support vector machine (SVM) [9], another learning by example method, can avoid these shortcomings of ANN by solving a ...
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