In this work, a bibliographic analysis on artificial neural networks (ANNs) using fractional
calculus (FC) theory has been developed to summarize the main features and applications …

This research proposes a novel transfer function based on the hyperbolic tangent and the
Khalil conformable exponential function. The non-integer order transfer function offers a …

This paper focuses on the growth, development, and future of various forms of fractional-
order neural networks. Multiple advances in structure, learning algorithms, and methods …

This paper focuses on deriving and validating the fractional‐order form of rectified linear unit
activation function and its linear and nonlinear variants. The linear variants include the leaky …

Energy efficient control of thermal comfort has been already an important part of residential
heating, ventilation, and air conditioning (HVAC) systems. However, the optimisation of …

A new physics-informed neural network (PINN) algorithm is proposed to solve variable-order
space-fractional partial differential equations (PDEs). For the forward problem, PINN …

The accuracy of state of charge estimation results will directly affect the performance of
battery management system. Due to such, we focus in this article on the SOC estimation of …

In the present work, a new fractional analytical scheme (NFAS) is developed to obtain the
approximate results of fourth-order parabolic fractional partial differential equations (FPDEs) …

In this paper, a numerical method based on the Müntz–Legendre polynomials for solving a
class of time-delay fractional optimal control problems (TDFOCPs) is presented. The concept …

The Hurst exponent is used to identify the autocorrelation structure of a stochastic time
series, which allows for detecting persistence in time series data. Traditional signal …