A model for bacterial population evaluation was built by using a back propagation neural network (BPNN) based on sensor responses from the E-nose.
The source laser produced 1030-nm 144-fs pulses which were coupled into Corning® HI 1060 fiber, whose length was chosen to be 40 cm by using a pulse propagation model based on solving the generalized nonlinear Schrödinger equation.
Our method introduced below overcomes this limitation by using a label propagation technique along with a protein-protein interaction network that includes these unannotated gene products.
But to address the concerted action of protein adsorption and lipid segregation, we extend this strategy here by using a dynamic propagation method to efficiently derive steady-state configurations for membranes interacting with macromolecules.
In the present work, the problems related to both the forward as well as reverse mappings in green sand mould system were tackled by using a back-propagation neural network (BPNN) and a genetic-neural network (GA-NN).
Each forward track propagates by using a Kalman filter propagation: begin{array}{l} left[bar {boldsymbol{x}}_{k|k-1},bar {boldsymbol{P}}_{k|k-1}right]=textbf{KF}_{mathrm{p}}left(hat {boldsymbol{x}}_{k-1|k-1},hat{boldsymbol{P}}_{k-1|k-1},boldsymbol{F},boldsymbol{Q}right) end{array} (9).
In this system, a fault identification framework is designed to identify automatically faulty network elements by using a two-level fault propagation model which combines Timing Constraint Petri nets with an alarm clustering mechanism.
Finally, by using a mixed-mode crack propagation simulation and two types of experimental information (loading-displacement response curve and crack path profile), the parameters of the cohesive zone model were inversely identified and its simulation results are in good agreement with the experiment.
By using a finite speed of propagation and specific estimates for the linear wave equations in (mathbb{R}^{n}), Feireisl obtained the existence of a global attractor for the semilinear wave equations with critical and supercritical exponents in an unbounded domain; see [18, 19].
