Application of Higher Order Ordinary Differential Equation Model in Financial Investment Stock Price Forecast

Zhang, Liqin; Xiao-jing, Tian

doi:10.2478/amns.2021.1.00074

Cited by 2 publications

(1 citation statement)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Eventually, modern IPTs have been instilled virtually in all felds for continuous optimization and have forced excellent improvements into the earlier procedures. In [69][70][71][72], the authors have presented the applications of higher-order diferential equations in fnancial and business predictions/forecasts based on the nonlinear and linear types of models. Figure 2 represents the complete structure of the hybrid solver for the singularly perturbed delay model.…”

Section: Learning Techniquesmentioning

confidence: 99%

Integrated Stochastic Investigation of Singularly Perturbed Delay Differential Equations for the Neuronal Variability Model

Ahmad,

Hussain,

Ilyas

et al. 2023

International Journal of Intelligent Systems

View full text Add to dashboard Cite

The proposed research utilizes a computational approach to attain a numerical solution for the singularly perturbed delay differential equation (SPDDE) problem arising in the neuronal variability model through artificial neural networks (ANNs) with different solvers. The log-sigmoid function is used to construct the fitness function. The implementation of ANN on SPDDE problems is formulated for different solvers and trained with different weights. The optimization solvers such as the genetic algorithm (GA), sequential quadratic programming (SQP), and pattern search (PS) are hybridized with the active set technique (AST) and the interior-point technique (IPT) and is used to check the accuracy and rapid convergence of the numerical results of the SPDDE model. The numerical outcomes demonstrate that the system is easy to handle and efficient to solve with boundary conditions. Moreover, we used the mean residual error for one hundred runs for each solver to validate the accuracy of the proposed scheme.

show abstract

Section: Learning Techniquesmentioning

confidence: 99%

Integrated Stochastic Investigation of Singularly Perturbed Delay Differential Equations for the Neuronal Variability Model

Ahmad,

Hussain,

Ilyas

et al. 2023

International Journal of Intelligent Systems

View full text Add to dashboard Cite

show abstract

A new approach for operations on neutrosophic soft sets based on the novel norms for constructing topological structures

Tran

Ngo

Bui

et al. 2022

MATH

View full text Add to dashboard Cite

<abstract> <p>Neutrosophic sets have recently emerged as a tool for dealing with imprecise, indeterminate, inconsistent data, while soft sets may have the potential to deal with uncertainties that classical methods cannot control. Combining these two types of sets results in a unique hybrid structure, a neutrosophic soft set (NS-set), for working effectively in uncertain environments. This paper focuses on determining operations on NS-sets through two novel norms. Accordingly, the $ {\rm{min}}-{\rm{n}}{\rm{o}}{\rm{r}}{\rm{m}} $ and $ {\rm{max}}-{\rm{n}}{\rm{o}}{\rm{r}}{\rm{m}} $ are well-defined here for the first time to construct the intersection, union, difference, AND, OR operations. Then, the topology, open set, closed set, interior, closure, regularity concepts on NS-sets are introduced based on these just constructed operations. All the properties in the paper are stated in theorem form, which is proved convincingly and logically. In addition, we also elucidate the relationship between the topology on NS-sets and the fuzzy soft topologies generated by the truth, indeterminacy, falsity degrees by theorems and counterexamples.</p> </abstract>

show abstract

Application of Higher Order Ordinary Differential Equation Model in Financial Investment Stock Price Forecast

Cited by 2 publications

References 12 publications

Integrated Stochastic Investigation of Singularly Perturbed Delay Differential Equations for the Neuronal Variability Model

Integrated Stochastic Investigation of Singularly Perturbed Delay Differential Equations for the Neuronal Variability Model

A new approach for operations on neutrosophic soft sets based on the novel norms for constructing topological structures

Contact Info

Product

Resources

About