With the development of urban and rural infrastructure, the power system is enforced to
operate nearly at its full capacity which result in heavily stressed power grid operation …

Forecasting of fast fluctuated and high-frequency financial data is always a challenging
problem in the field of economics and modelling. In this study, a novel hybrid model with the …

Background: Mathematical modeling of vector-borne diseases and forecasting of epidemics
outbreak are global challenges and big point of concern worldwide. The outbreaks depend …

In this paper, the design of stochastic computational intelligent solver is presented for the
solution of mathematical model representing the dynamics of mosquito dispersal in a …

In this study, a new computing model is developed using the strength of feed‐forward neural
networks with the Levenberg–Marquardt scheme‐based backpropagation technique (NN …

The present study aims to design stochastic intelligent computational heuristics for the
numerical treatment of a nonlinear SITR system representing the dynamics of novel …

The aim of this work is to design an intelligent computing paradigm through Levenberg–
Marquardt artificial neural networks (LMANNs) for solving the mathematical model of Corona …

In this study, bio-inspired computational techniques have been exploited to get the
numerical solution of a nonlinear two-point boundary value problem arising in the modelling …

In this research article, artificial neural networks back-propagated with Levenberg Marquardt
scheme (ANN-BLMS) is presented to analyze the entropy generation of carbon nanotubes …

In the present study, a novel fractional Meyer neuro-evolution-based intelligent computing
solver (FMNEICS) is presented for numerical treatment of doubly singular multi-fractional …