least-squares model-based algorithm
Least Squares Matrix Algorithm for State Space Modelling of Dynamic Systems
... novel least squares matrix algorithm (LSM) for the analysis of rapidly changing systems using state-space ...LSM algorithm is based on the Hankel structured data matrix ...of ...
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Data filtering-based least squares iterative algorithm for Hammerstein nonlinear systems by using the model decomposition
... decomposition based least squares iterative algorithm is presented for estimating the parameter vectors in each ...filtering based decomposition least squares iterative ...
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Predicting bruise susceptibility in apples using Vis/SWNIR technique combined with ensemble learning
... thickness model. Three prediction models, i.e. partial least squares model (PLS), partial least squares model combined with successful projection algorithm ...
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Newton Krylov Type Algorithm for Solving Nonlinear Least Squares Problems
... an algorithm for solving nonlinear least squares ...This algorithm is based on constructing a basis for the Krylov subspace in conjunction with a model trust region technique to ...
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A Robust Collaborative Recommendation Algorithm Based on Least Median Squares Estimator
... neighborhood model among items, and temporal effects ...neighborhood model are vulnerable to shilling attacks. Moreover, the least squares estimator is sensitive to ...
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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
... forecasting model based on the improved least squares support vector machine (ILSSVM) optimized by wolf pack algorithm(WPA) is proposed to improve the accuracy and stability of the cost ...
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NEW MODEL TRANSFORMATION USING REQUIREMENT TRACEBILITY FROM REQUIREMENT TO UML BEHAVIORAL DESIGN
... fitting least squares serial algorithm, based on the least square principle we found an parallel least squares curve and surface fitting method; Second, further reform the ...
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Segmentation algorithm for Hangzhou white chrysanthemums based on least squares support vector machine
... chrysanthemum based on least squares support vector machine (LS-SVM) was ...LS-SVM model (classifier) and SVM model (classifier), were extracted via RGB value of image and gray level ...
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The design of parallel least squares model based on the surface fitting problem
... serial algorithm tend to be complicated, waste of time and not easy to ...the least square parameter estimation of parallel algorithm from parameter estimation, Zhixia Yang presents a new parallel ...
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Recursive Least Squares Dictionary Learning Algorithm for Electrical Impedance Tomography
... The samples used to learn the initial dictionary are constructed with COMSOL Multiphysics software. Three kinds of training data are created, as shown in Figure 1. The imaging area of the model is a circular area ...
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Combined state and parameter estimation for Hammerstein systems with time-delay using the Kalman filtering
... over-parameterization model based stochastic gradient algorithm to obtain the parameter estimates, but they did not consider the process noise and the time-delay in the model structure ...
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Analysis of partial least squares algorithm based on SBM DEA
... PLS model, which improves the model precision and calculate the efficiency value of the sample points depending on SBM as well as analyze its characteristics, therefore, the “bad data” can be eliminated ...
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Particle swarm optimized partial least square support vector regression model for tax revenue prediction
... is based on the basic characteristics of China’s economic operation, taking advantage of the support vector machine and the particle swarm these two intelligent optimization ...swarm algorithm to ...
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A Partial Least Squares based algorithm for parsimonious variable selection
... elimination algorithm for variable selection using Partial Least Squares, where the focus is to obtain a hard, and at the same time stable, selection of ...selected model, model ...
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A Comparison of Univariate ARIMA and Multivariate to Estimate Absorption Pattern in Stronsium Tittanate Dop Variation
... to model the observation series and variable dop containing spatial dependence between its ...to model and assess the accuracy of forecasting of the ARIMA, VARIMA, and GSTARIMA using space weight is ...
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A New Algorithm for Generalized Least Squares Factor Analysis with a Majorization Technique
... inequality-based algorithm has not been developed for the GLS estima- tion in which (4) is minimized over Θ ...The algorithm to be proposed is also computationally simple as in the existing ...
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Rapid detection of total nitrogen content in soy sauce using NIR spectroscopy
... A method for the rapid and nondestructive determination of total nitrogen content in soy sauce was explored. Pre- diction models were established using near-infrared spectroscopy combined with each of the following ...
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Least Squares Filtering Algorithm for Reactive Near Field Probe Correction
... Constrained Least Squares Filtering Method compared with the Direct Inverse Filtering technique, we consider a situation for which the actual device under test radiated electric field and the exact probe ...
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A general order multichannel, fast least squares algorithm with telecommunications applications
... It was derived using the recursive form of (2.6) and the matrix inversion lemma [52), which generates an explicit inverse formula for matrices of a certain type. The algorithm sequence i[r] ...
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Fitting Data with Different Error Models »
... The numerical computations show that the formulas developed by an ML estimator via symbolic computation to determine the parameters of a straight line to be fitted provide correct results and require considerably less ...
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