Results 271 to 280 of about 10,133,028 (343)
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, 2020
Accurate forecasting of the combined loads of electricity, heat, cooling and gas in the integrated energy system is the key to improve the comprehensive efficiency and gain more economic benefits of various types of energy.
Z. Tan +6 more
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Accurate forecasting of the combined loads of electricity, heat, cooling and gas in the integrated energy system is the key to improve the comprehensive efficiency and gain more economic benefits of various types of energy.
Z. Tan +6 more
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Least squares estimates and the coverage of least squares costs
52nd IEEE Conference on Decision and Control, 2013The least squares estimate xN minimizes the sum of the squared residuals equation over a finite set of observations (Ai, bi). At x = xN, the squared residuals ∥AixN-bi∥2 are called the “empirical costs”. Intuitively, the empirical costs carry information on the probability distribution of the cost ∥AxN-b∥2 that is paid for other, yet unseen, values of (
Carè, Algo +2 more
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Proceedings Shape Modeling Applications, 2004., 2004
In this paper we introduce least-squares meshes: meshes with a prescribed connectivity that approximate a set of control points in a least-squares sense. The given mesh consists of a planar graph with arbitrary connectivity and a sparse set of control points with geometry. The geometry of the mesh is reconstructed by solving a sparse linear system. The
Olga Sorkine, Daniel Cohen-Or
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In this paper we introduce least-squares meshes: meshes with a prescribed connectivity that approximate a set of control points in a least-squares sense. The given mesh consists of a planar graph with arbitrary connectivity and a sparse set of control points with geometry. The geometry of the mesh is reconstructed by solving a sparse linear system. The
Olga Sorkine, Daniel Cohen-Or
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The Inefficiency of Least Squares
Biometrika, 1975SUMMARY Two criteria are set up to judge the relative performance of the least squares estimator and the best linear unbiased estimator of , in the linear model y = X/, + u, where E(u) = 0, E(uu') = F. The matrices X and r are found so that the relative performance of least squares is worst.
Bloomfield, Peter, Watson, Geoffrey S.
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2016
The English version of this paper appeared two years after the Chinese “original”. During the 1950s and early 1960s, DDK visited China several times on exchange programmes.
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The English version of this paper appeared two years after the Chinese “original”. During the 1950s and early 1960s, DDK visited China several times on exchange programmes.
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, 2016
This paper presents a new and hybrid algorithm based on Firefly Algorithm (FA) and Recursive Least Square (RLS) for power system harmonic estimation. The hybrid FA–RLS algorithm is developed for estimating harmonics, inter harmonics and sub harmonics ...
S. Singh +3 more
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This paper presents a new and hybrid algorithm based on Firefly Algorithm (FA) and Recursive Least Square (RLS) for power system harmonic estimation. The hybrid FA–RLS algorithm is developed for estimating harmonics, inter harmonics and sub harmonics ...
S. Singh +3 more
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Information Sciences, 1988
The author discusses three models of fuzzy linear regression function for triangular fuzzy numbers [Fuzzy numbers with triangular shapes, cf. \textit{D. Dubois} and \textit{H. Prade}, Int. J. Syst. Sci. 9, 613-626 (1978; Zbl 0383.94045)]. Formulas are deduced by the least-squares method.
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The author discusses three models of fuzzy linear regression function for triangular fuzzy numbers [Fuzzy numbers with triangular shapes, cf. \textit{D. Dubois} and \textit{H. Prade}, Int. J. Syst. Sci. 9, 613-626 (1978; Zbl 0383.94045)]. Formulas are deduced by the least-squares method.
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Computers & Graphics, 1978
Abstract The method of least-squares is intended to fit a function to a set of data points closely, so as to satisfy a particular criterion of closeness. The approximating function can be taken to be a linear combination of linearly independent functions of an independent variable.
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Abstract The method of least-squares is intended to fit a function to a set of data points closely, so as to satisfy a particular criterion of closeness. The approximating function can be taken to be a linear combination of linearly independent functions of an independent variable.
openaire +2 more sources