accurate calculation of reliability index is very important for the reliability analysis of structures. in some limit state functions with nonlinear characteristic and several local optimum design points, the computational reliability methods may not appropriately determine the failure probability, and iterative reliability approaches may be converged to local optimum design points. in this pap...

Applying nonlinear models to estimation and forecasting economic models are now becoming more common, thanks to advances in computing technology. Artificial Neural Networks (ANN) models, which are nonlinear local optimizer models, have proven successful in forecasting economic variables. Most ANN models applied in Economics use the gradient descent method as their learning algorithm. However, t...

Nonlinear conjugate gradient method is well known in solving large-scale unconstrained optimization problems due to it’s low storage requirement and simple to implement. Research activities on it’s application to handle higher dimensional systems of nonlinear equations are just beginning. This paper presents a Threeterm Conjugate Gradient algorithm for solving Large-Scale systems of nonlinear e...

We discuss the feedback algorithm for optogenetic control over membrane conductance in frame of Grossman-Nikolic-Toumazou-Degenaar (GNTD) ordinary differential system modeling response channelrhodopsin-2 (ChR2) expressing neurons to light stimulation with various types ChR2 mutants. The GNTD population dynamics contains four functional states (two open and two closed) transitions among them due...

applying nonlinear models to estimation and forecasting economic models are now becoming more common, thanks to advances in computing technology. artificial neural networks (ann) models, which are nonlinear local optimizer models, have proven successful in forecasting economic variables. most ann models applied in economics use the gradient descent method as their learning algorithm. however, t...