A Novel Design of Morlet Wavelet to Solve the Dynamics of Nervous Stomach Nonlinear Model

Abstract

The present study introduces a novel design of Morlet wavelet neural network (MWNN) models to solve a class of a nonlinear nervous stomach system represented with governing ODEs systems via three categories, tension, food and medicine, i.e., TFM model. The comprehensive detail of each category is designated together with the sleep factor, food rate, tension rate, medicine factor and death rate are also provided. The computational structure of MWNNs along with the global search ability of genetic algorithm (GA) and local search competence of active-set algorithms (ASAs), i.e., MWNN-GA-ASAs is applied to solve the TFM model. The optimization of an error function, for nonlinear TFM model and its related boundary conditions, is performed using the hybrid heuristics of GA-ASAs. The performance of the obtained outcomes through MWNN-GA-ASAs for solving the nonlinear TFM model is compared with the results of state of the article numerical computing paradigm via Adams methods to validate the precision of the MWNN-GA-ASAs. Moreover, statistical assessments studies for 50 independent trials with 10 neuron-based networks further authenticate the efficacy, reliability and consistent convergence of the proposed MWNN-GA-ASAs.

Fractional Order Nonlinear Bone Remodeling Dynamics Using the Supervised Neural Network

“…In this section, the existing section shows the stochastic operator performances for solving the fractional order computational myeloma bone disease model with LVMBPNN. In the literature, stochastic software solvers have been investigated to solve complicated, singular, and rigid systems [42,43]. Recently, the simulation based on the food chain function [44], infection control model [45], Lane-Emden systems [46], functional order approaches [47], and nonlinear dynamic HIV systems [48][49][50].…”

Numerical Simulations of Vaccination and Wolbachia on Dengue Transmission Dynamics in the Nonlinear Model

“…In this section, the statistical operator characteristics relying on ''Theil's inequality coefficient (TIC)'', ''Variance account for (VAF)'', ''Mean absolute deviation (MAD)'', and ''Semi interquartile range (S.I.R)'' are theoretically described in order to solve dengue mathematical model. ( 19)- (21), as shown at the bottom of pages 10 and 11, respectively. S.I Range = 0.5 × (q 3 − q 1 ) ,…”

“…The objective of this research is to explore a mathematical model of vaccination and Wolbachia used for dengue transmission and dispersal and its analysis in the form of simulation solutions to assist in understanding dynamic behavior using a stochastic technique. Exploring the prospect of fixing linear/nonlinear systems using the high predictive capabilities of feedforward artificial neural networks (ANNs) optimized with the combined capabilities of local/global search methods is a significant potential of meta-heuristic computing paradigm based on stochastic approach [21]- [23]. Soft computing techniques reported in different diseases such as Convolution neural networks for analysis of plant diseases [24], [25], for COVID-19 disease [26]- [29], artificial neural networks for tuberculosis [30], for forecasting disease [31], for skin diseases [32], chest disease [33], for diagnosis of kidney stone diseases [34], respiratory disease [35], for HIV infection [36], to analyze influenza disease model [37] and for stomach model [38].…”

An Intelligence Computational Approach for the Fractional 4D Chaotic Financial Model

“…For example, El-Mahelawi et al [19] investigated the solution of some model classifications using the tumors. Sabir et al [20] adapted the Morlet wavelet neural network for solving a class of nonlinear system to simulate the nervous stomach system. Also, biology has its share of the simulations done with the aid of these methods.…”