Annalen der PhysikVolume 535, Issue 2 2370003 Cover PictureFree Access (Ann. Phys. 2/2023) First published: 16 February 2023 https://doi.org/10.1002/andp.202370003AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text full-text accessPlease review our Terms and Conditions of Use check box below share version article.I have read accept...

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...

Efficient time series forecasting (TSF) is of utmost importance in order to make better decision under uncertainty. Over the past few years a large literature has evolved to forecast time series using different artificial neural network (ANN) models because of its several distinguishing characteristics. This paper evaluates the effectiveness of three methods to forecast time series, one carried...

Artificial neural networks (ANN) have received a great deal of attention in many fields of engineering and science. Inspired by the study of brain architecture, ANN represent a class of nonlinear models capable of learning from data. ANN have been applied in many areas where statistical methods are traditionally employed. They have been used in pattern recognition, classification, prediction an...

Supported education may be defined as the provision of support and services to help persons with psychiatric disabilities gain access to and succeed in a postsecondary college or technical school. Since recovery-oriented services are those that support individuals in reclaiming their lives in the community and overcoming the effects of being perceived as mental patients (Tondora & Davidson, 200...