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Systems efficiency is easily affected by the changes in solar radiation so, this study is aimed to develop a Least Squares Support Vector Machine (LS-SVM) based intelligent model to predict the next day's solar insolation for taking measures.
Over 80% of children develop a least one incident of OM by three years of age and more than half of children experience multiple episodes of this disease [1], [2].
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In this paper, Geographic Information System (GIS) tools were used to develop a least-cost path for a corridor to link three cities in Sinai Peninsula desert environment.
We further develop a least-squares version of this approach in order to obtain a non-iterative procedure to obtain the inverse projection.
This paper addresses the problem of developing a least mean squares (LMS) style decision feedback equaliser algorithm for minimising bit error rate (BER) in impulsive noise environments characterised by the α-stable distribution.
This paper developed a least-squares method to evaluate the mixed-mode stress intensity factors (SIFs) of the isotropic material using the computer images from the digital-camera experiment.
For example, C. Xu et al developed a least-squares algorithm for SOCT to separate absorption and scattering [ 35].
In that way, we have considered a set of 23 complexes comprising biotin and urea derivatives with synthetic hosts to develop a Partial Least Squares Cross-Validated (PLS-CV) model.
Hence, we can develop a weighted least squares algorithm as described below.
External parameter orthogonalization — EPO — was used in developing a partial least squares regression (PLSR) model to predict clay and organic C contents of soil samples with variable moisture contents.
To further investigate the TAG accumulation in the cells, we have developed a partial least square regression (PLSR) model to quantify the TAG content in individual Group N- cells at different time points.
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