Abstract: This paper proposes an improved second order (ISO) algorithm for training radial basis function (RBF) networks. Besides the traditional parameters, including centers, widths and output ...
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New computational method combines modern density functional with adaptive algorithm to predict semiconductor properties
Semiconductors are central to modern technology. They are used in computer chips, solar cells, sensors, LEDs and ...
Abstract: The radial basis function network-based autoregressive with exogenous input (RBF-ARX) model is the nonlinear model based on state dependence with additional input. This brief discusses the ...
Genome editing lets scientists rewrite DNA, the instruction manual inside every living cell, with a precision that was unthinkable a generation ago. Technologies such as CRISPR have made this almost ...
Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.
See my DrGFreeman/rps-cv-data-science repository where I posted different notebooks demonstrating some cool data science analysis on the image dataset resulting from this project. This project results ...
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Parameters for the k-GTM algorithm are the square root of the number of grid points (k), the square root of the number of RBF functions (m), the regularization coefficient (l), the RBF width factor (w ...
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