Modeling and forecasting are impressive and active research areas, which have been
widely used in diverse theoretical and practical applications, successfully. Accuracy is the …

Echo state network (ESN) is a reservoir computing structure consisting randomly generated
hidden layer which enables a rapid learning and extrapolation process. On the other hand …

We explore various neural network architectures for modeling the dynamics of the
cryptocurrency market. Traditional linear models often fall short in accurately capturing the …

In this paper, we present a recurrent neural system named long short-term cognitive
networks (LSTCNs) as a generalization of the short-term cognitive network (STCN) model …

With the large-scale development of electric vehicles, the accuracy of electric vehicle
charging load prediction is increasingly important for electric power system. Accurate EV …

Recently, researchers have used various methods for time-series forecasting based on
artificial neural network models. Among these approaches, one of the most effective ones is …

In this paper, we present a recurrent neural system named Long Short-term Cognitive
Networks (LSTCNs) as a generalization of the Short-term Cognitive Network (STCN) model …

This research harnesses advancements in deep learning (DL) and statistical analysis to
present a novel approach that focuses on employing a mixture model for the prediction of …

To solve the problems of delayed prediction results and large prediction errors in one-
dimensional time series prediction, a time series prediction method based on Error …

This thesis, structured in four distinct parts, contributes to enriching the fields of deep
learning and nonlinear econometrics. Traditional models have often shown weaknesses in …