Results 231 to 240 of about 173,770 (295)

NifFinder: improved Nif protein prediction using SWeeP vectors and neural networks. [PDF]

Bioinform Adv
de Lima Nichio BT, Chaves RBR, Marchaukoski JN, Pedrosa FO, Raittz RT.   +4 more
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A novel stacking ensemble model for predicting discharge coefficient of submerged multi parallel radial gates. [PDF]

Sci Rep
Abdelazim NM, Hosny M, Abdelhaleem FS, Elshenhab AM, Ibrahim A.   +4 more
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Modeling tumor transport and growth with poroelastic biopolymer networks.

Soft Matter
Li Z, Ren Y, Kemkar S, Mollenkopf P, Kochanowski J, Janmey PA, Purohit PK, Radhakrishnan R, Vining KH.   +8 more
europepmc   +1 more source

A multiscale framework for developing equations of state of supercritical aqueous systems from synchrotron experiments, atomistic simulations, and machine learning

Karalis K, Churakov SV, Prasianakis N, Maxim F, Cervellino A, Temleitner L, Pusztai L, Tzampoglou P, Krack M, Ludwig C, Niceno B.   +10 more
europepmc   +1 more source

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Radial Basis Function Networks

2013
Learning is an approximation problem, which is closely related to the conventional approximation techniques, such as generalized splines and regularization techniques. The RBF network has its origin in performing exact interpolation of a set of data points in a multidimensional space [81].
Ke-Lin Du, M. N. S. Swamy
openaire   +2 more sources

Median radial basis function neural network

IEEE Transactions on Neural Networks, 1996
Radial basis functions (RBFs) consist of a two-layer neural network, where each hidden unit implements a kernel function. Each kernel is associated with an activation region from the input space and its output is fed to an output unit. In order to find the parameters of a neural network which embeds this structure we take into consideration two ...
A G, Bors, I, Pitas
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