Machine intelligence in dynamical systems:\A state‐of‐art review
AK Sahoo, S Chakraverty - Wiley Interdisciplinary Reviews …, 2022 - Wiley Online Library
This article is dedicated to study the impact of machine intelligence (MI) methods viz. various
types of Neural models for investigating dynamical systems arising in interdisciplinary areas …
types of Neural models for investigating dynamical systems arising in interdisciplinary areas …
Deep neural network methods for solving forward and inverse problems of time fractional diffusion equations with conformable derivative
Y Ye, H Fan, Y Li, X Liu, H Zhang - Neurocomputing, 2022 - Elsevier
Fractional diffusion equations with conformable derivative have become an important
research topic in Newtonian mechanics, quantum mechanics, arbitrary time scale problems …
research topic in Newtonian mechanics, quantum mechanics, arbitrary time scale problems …
[PDF][PDF] Modeling of Mexican hat wavelet neural network with L-BFGS algorithm for simulating the recycling procedure of waste plastic in ocean
AK Sahoo, S Chakraverty - Journal of Engineering …, 2023 - library.acadlore.com
In the global economy, plastics are considered a versatile and ubiquitous material. It can
reach to marine ecosystems through diverse channels, such as road runoff, wastewater …
reach to marine ecosystems through diverse channels, such as road runoff, wastewater …
Stabilised auto-regressive neural networks (s-ARNNs) for data driven prediction of forced nonlinear systems
Forced vibrations of nonlinear dynamical systems are usually predicted by solving
differential equations, which have been derived from 'first principles' given by physical laws …
differential equations, which have been derived from 'first principles' given by physical laws …
Neural network methods based on efficient optimization algorithms for solving impulsive differential equations
B Xing, H Liu, X Tang, L Shi - IEEE Transactions on Artificial …, 2022 - ieeexplore.ieee.org
In view of the fact that impulsive differential equations have the discreteness due to the
impulse phenomenon, this article proposes a single hidden layer neural network method …
impulse phenomenon, this article proposes a single hidden layer neural network method …
Solving Emden–Fowler Equations Using Improved Extreme Learning Machine Algorithm Based on Block Legendre Basis Neural Network
Y Yang, Y Wu, M Hou, J Luo, X Xie - Neural Processing Letters, 2023 - Springer
In this paper, a numerical method to solve second order nonlinear ordinary differential
equations with singular initial value problems was proposed. Here, block Legendre basis …
equations with singular initial value problems was proposed. Here, block Legendre basis …
Comparative study of Chebyshev and Legendre polynomial-based neural models for approximating multidimensional poverty for an Indian State
The objective of this chapter is to analyse different neural models for estimating the condition
of multidimensional poverty in an Indian state viz. Odisha. In this regard, two functional link …
of multidimensional poverty in an Indian state viz. Odisha. In this regard, two functional link …
Patent trends in nanobiotechnology applications in the livestock industry
The application of nanomaterials, processes, and products in biological systems is known as
bionanotechnology. It has tremendous potential in terms of more precise and practical …
bionanotechnology. It has tremendous potential in terms of more precise and practical …