[PDF] Top 20 INSTRUMENTO PARA EVALUAR EL NIVEL DE SATISFACCIÓN EN LOS USUARIOS DE LOS SERVICIOS ASISTENCIALES
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Simulated annealing least squares twin support vector machine (SA LSTSVM) for pattern classification
... Abstract Least squares twin support vector machine (LSTSVM) is a relatively new version of support vector machine (SVM) based on non-parallel twin ... See full document
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Simulated annealing least squares twin support vector machine (SA LSTSVM) for pattern classification
... nonparallel twin hy- ...binary classification, its parameters depend on the nature of the ...gorithm. Simulated Annealing (SA) is a random search technique proposed to find the global minimum ... See full document
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Classification of Clustered Microcalcifications in Mammograms using Particle Swarm Optimization and Least Squares Support Vector Machine
... two-class pattern recognition problem accomplished in four steps, namely, preprocessing and region of interest selection, feature extraction, feature selection, differentiating between malignant and benign ... See full document
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Using Least Squares Support Vector Machines for Frequency Estimation
... a pattern recognition problem, and a least squares support vector machine (LS-SVM) estimator is ...since classification-based method does not have the threshold effect of ... See full document
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Analysis of Ammonia Nitrogen Content in Water Based on Weighted Least Squares Support Vector Machine (WLSSVM) Algorithm
... weighted least squares support vector machine algo- ...weighted least squares support vector machine algorithm increases the weight para- meter ... See full document
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The application of the support vector machine to the classification
... Result The misclassification rate of 0.0091 for decision tree and 0.138 for SVM indicate that Support Vector Machine does not perform as well as the decision tree for this set of data 0.[r] ... See full document
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Comparison of Classification Algorithms using Machine Learning
... Machine learning systems itself grasp programs or plan from data. This is generally a very impressive alternative to making or substitute constructing them and in the last some past years the utilizing of ... See full document
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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
... Spectrophotometric analysis was carried out on T90+UV/vis, PG instruments Ltd. double beam spectrophotometer equipped with 1.0 cm quartz cells. HPLC system (Agilent 1260) with UV detector was used. Separation was ... See full document
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A novel fault-tolerant control strategy for near space hypersonic vehicles via least squares support vector machine and backstepping method
... The Backstepping is a recursive design method [16-17,19]. It needs to simplify the nonlinear system in strict feedback form of differential equations early in the controller design. After specifying the control ... See full document
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On the ease of predicting the thermodynamic properties of beta-cyclodextrin inclusion complexes
... In this study we investigated the predictability of the experimental thermodynamic data for 176 guest mole- cules of β -CD (see additional file 1: Table 1). For all mol- ecules we had experimental values for the three ... See full document
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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
... paper, Least Square Support Vector Regression (LSSVR) model based on Coupled Simulated Annealing (CSA) has been successfully used to nd the nonlinear relationship between the concrete ... See full document
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Detection of Masquerade Attack by Data Driven Semi-Global Alignment Approach
... Masquerade attackers behave like a authorized user to utilize user requirements. The semi-global alignment algorithm (SGA) is one of the most optimize and unique techniques to find out these attack but it has not extend ... See full document
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Applying ANN, ANFIS, and LSSVM Models for Estimation of Acid Solvent Solubility in Supercritical CO
... network, Least squares support vector machine and adaptive neuro-fuzzy inference system are developed to predict the solubility of different acids in carbon dioxide based on the ... See full document
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Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis
... The posterior obtained is not equivalent to FLD because the mean of w is zero. In consequence, the posterior mean projection of any x ? will collapse to the origin. Nonetheless, this formulation yields a consistent ... See full document
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Algorithm Model and Performance Evaluation of P2P Network System under the Internet of Things
... Chord redundancy: Redundancy means that there is a garbage item in the Finger table of Chord, and the items between Node N and its successor are meaningless because the successor represented by these items does not ... See full document
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The Corporate Financial Forecasting Based on Least Squares Support Vector Machines Methods
... as the problem that how to ascertain the network structure, the over-fitting problem, the local minima problem. These are essentially because the contradic- tions of infinite sample in theory and finite sample in ... See full document
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Forgery Detection of Spliced Images Using Machine Learning Classifiers and color Illumination
... techniques are proposed. The most effective tool for providing image realism and source details is digital watermarking. Image Forgery detection is also solved by these digital watermarks. Various watermarking techniques ... See full document
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River flow time series using least squares support vector machines
... The data-driven models such as artificial neural networks (ANN) have recently been accepted as an efficient alternative tool for modelling a complex hydrologic system compared with the conventional methods and is widely ... See full document
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Using Principal Component Analysis and Least Squares Support Vector Machine to Predict the Silicon Content in Blast Furnace System
... partial least squares model[8], mathematical model of mul- tifluid theory[9], support vector machine and intelligent algorithm cross model[10], wavelet analysis model ... See full document
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Copy move image classification by feature optimization with support vector machine approach
... Authors utilize DCT-phase terms to restrict the range of the feature vector elements’ and Benford’s generalized law to determine the compression history of the image under test. The method uses element-by-element ... See full document
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