Huda M Alshanbari

Abstract Electricity spot prices are found to be highly long-range dependent, with hyperbolically decaying instead of geometrically decaying autocorrelation functions that challenge traditional functional time series models of forecasting. In existing hybrid forecasting frameworks, the stochastic intraday part is usually modeled by first-order Functional Autoregressive (FAR(1)) models, which have a short memory structure which fails to capture the temporal dependence adequately.

Abstract This paper presents a complete EEG encryption framework based on a newly designed fractional variable-order memristive hyperchaotic system. The proposed system exhibits high-dimensional nonlinear dynamics with tunable memory effects, making it highly suitable for cryptographic operations requiring strong sensitivity, unpredictability, and large keyspace.

Data Availability Statement The datasets that are to be used in this study can be requested at reasonable demand by the concerned author. Such datasets are made available to foster additional questioning, confirmation, or elaboration of the study to enhance transparency and allow other people to reproduce or extend the results of the research.