A Derivation of Backpropagation in Matrix Form(转) Backpropagationis an algorithm used to train neural networks, used along with an optimization routine such asgradient descent. Gradient descent requires access to the gradient of the loss function with respect to all the weights in the network to...
backtrack algorithmsconstraint propagationformal specificationprogram synthesisscheduling algorithmsIn this paper we describe the formal derivation of a transportation scheduling algorithm. The algorithm is based on the concepts of global search and constraint propagation and was originally derived using kids (...
The algorithm is a neural network (NN) which is used to parameterize the inverse of a radiative transfer model. It is used in this study as a multiple nonlinear regression technique. The NN is a feedforward backpropagation model with two hidden layers. The NN was trained with computed ...
All of these works used the back-propagation algorithm (Rumelhart et al., 1986) for training the ANNs and compared the results with some of the most popular sediment transport formulae. For all the cases, the ANNs generated superior results. 2.2. Symbolic regression based on genetic programming...
FIG. 9 is a flow chart of an algorithm900for resource deployment in accordance with an exemplary embodiment of the present disclosure. Algorithm900can be implemented in hardware or a suitable combination of hardware and software, and can be one or more algorithms operating on one or more process...
We develop a practical forward fitting method based on the SIMPLEX algorithm with shaking, which allows the derivation of the magnetic field and other para... GD Fleishman,GM Nita,DE Gary - 《Astrophysical Journal》 被引量: 22发表: 2009年 THE GYROKINETIC APPROXIMATION FOR THE VLASOV–POISSON SY...
Different neural assemblies (reflecting distinct eigenvectors of the connectivity matrices) can simultaneously and independently display different properties in terms of stability, propagation speed or direction. We also derive continuous-limit versions of the system, both in time and in neural space. ...
Recursive auto-associative memory (RAAM) has become established in the connectionist literature as a key contribution in the strive to develop connectionist representations of symbol structures. However, RAAMs use the backpropagation algorithm and therefore can be difficult to train and slow to learn. ...
On the numerical algorithm for isotropic-kinematic hardening with the Armstrong-Frederick evolution of the back stress Comput. Methods Appl. Mech. Engrg., 2002, 191: 3583-3596.LUBARDA, V.A., BENSON, D.J., On the numerical algorithm for isotropic-kinematic hardening... V Lubarda - European ...
Using backpropagation neural network (BPNN) to derive marine water quality criteria.The BPNN model demonstrated flexibility and accuracy compared to the MNLR model.The BPNN model has shown good potential in handling species-specific effects.The WQC range of copper under natural marine environments cond...