Open AccessGeneralized Dai-Yuan conjugate gradient algorithm for training multi-layer feed-forward neural networks
Author(s) -
Hind H. Mohammed
Publication year - 2019
Publication title -
mağallaẗ tikrīt li-l-ʻulūm al-ṣirfaẗ/tikrit journal of pure science
Language(s) - Uncategorized
Resource type - Journals
eISSN - 2415-1726
pISSN - 1813-1662
DOI - 10.25130/j.v24i1.789
Subject(s) - conjugate gradient method , gradient descent , convergence (economics) , artificial neural network , algorithm , conjugacy class , computer science , nonlinear conjugate gradient method , training (meteorology) , field (mathematics) , layer (electronics) , stochastic gradient descent , backpropagation , descent (aeronautics) , artificial intelligence , mathematics , combinatorics , geography , meteorology , pure mathematics , chemistry , organic chemistry , economics , economic growth