Hybrid networks in which living neurons interact with digital or analog model neurons are providing insights into the role of neural and synaptic properties in shaping neural network activity.

in the present study, a model of a large lithium polymer (li-po) battery for use in the simulation of hybrid electric vehicles (hevs) is developed. to attain this goal, an equivalent circuit (ec) consisting of a series resistor and two rc parallel networks is considered. the accuracy and the response time of the model for use in an hev simulator are studied. the battery parameters identificatio...

Computational intelligence approaches have gradually established themselves as a popular tool for forecasting the complicated financial markets. Forecasting accuracy is one of the most important features of forecasting models; hence, never has research directed at improving upon the effectiveness of time series models stopped. Nowadays, despite the numerous time series forecasting models propos...

Abstract This paper presents a new class of Bayesian networks called hybrid semiparametric networks, which can model data (discrete and continuous data) by mixing parametric nonparametric estimation models. The models represent conditional linear Gaussian relationship between variables, while the other types relationships, such as non-Gaussian nonlinear relationships. generalizes including them...

in this paper, we introduce a hybrid approach based on neural network and optimization teqnique to solve ordinary differential equation. in proposed model we use heyperbolic secont transformation function in hiden layer of neural network part and bfgs teqnique in optimization part. in comparison with existing similar neural networks proposed model provides solutions with high accuracy. numerica...

A comparison of corporate failure models in Australia: Hybrid neural networks, logit models and discriminant analysis. A comparison of corporate failure models in Australia: Hybrid neural networks, logit models and discriminant analysis. Abstract This study investigated whether two artificial neural networks (ANNs), multilayer perceptron (MLP) and hybrid networks using statistical and ANN appro...

The use of intelligent network technology and hybrid networks that include intelligent networks has created new challenges for those who wish to integrate heterogeneous databases distributed across these networks. Advances in public network technology enable the implementation of new distributed database systems that require improved query distribution and optimization algorithms. Reducing resp...