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

AbstractThe 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.

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Numerical Computing Paradigm for Investigation of Micropolar Nanofluid Flow Between Parallel Plates System with Impact of Electrical MHD and Hall Current

Arabian Journal for Science and Engineering ◽

10.1007/s13369-020-04736-8 ◽

2020 ◽

Vol 46 (1) ◽

pp. 645-662 ◽

Cited By ~ 1

Author(s):

Saeed Ehsan Awan ◽

Muhammad Asif Zahoor Raja ◽

Faiza Gul ◽

Zuhaib Ashfaq Khan ◽

Ammara Mehmood ◽

...

Keyword(s):

Hall Current ◽

Parallel Plates ◽

Nanofluid Flow ◽

Computing Paradigm ◽

Micropolar Nanofluid ◽

Numerical Computing

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A Neuro-Evolution Heuristic Using Active-Set Techniques to Solve a Novel Nonlinear Singular Prediction Differential Model

Fractal and Fractional ◽

10.3390/fractalfract6010029 ◽

2022 ◽

Vol 6 (1) ◽

pp. 29

Author(s):

Zulqurnain Sabir ◽

Muhammad Asif Zahoor Raja ◽

Thongchai Botmart ◽

Wajaree Weera

Keyword(s):

Numerical Solutions ◽

Mean Squared Error ◽

Merit Function ◽

The Novel ◽

Active Set ◽

Shape Factors ◽

Differential Model ◽

Squared Error ◽

Global And Local ◽

Novel Design

In this study, a novel design of a second kind of nonlinear Lane–Emden prediction differential singular model (NLE-PDSM) is presented. The numerical solutions of this model were investigated via a neuro-evolution computing intelligent solver using artificial neural networks (ANNs) optimized by global and local search genetic algorithms (GAs) and the active-set method (ASM), i.e., ANN-GAASM. The novel NLE-PDSM was derived from the standard LE and the PDSM along with the details of singular points, prediction terms and shape factors. The modeling strength of ANN was implemented to create a merit function based on the second kind of NLE-PDSM using the mean squared error, and optimization was performed through the GAASM. The corroboration, validation and excellence of the ANN-GAASM for three distinct problems were established through relative studies from exact solutions on the basis of stability, convergence and robustness. Furthermore, explanations through statistical investigations confirmed the worth of the proposed scheme.

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Design Multipurpose Circuits with Minimum Garbage Outputs Using CMVMIN Gate

Chinese Journal of Engineering ◽

10.1155/2014/532121 ◽

2014 ◽

Vol 2014 ◽

pp. 1-7 ◽

Cited By ~ 2

Author(s):

Bahram Dehghan

Keyword(s):

Logic Gates ◽

Quantum Cost ◽

Computing Paradigm ◽

Novel Approach ◽

Half Adder ◽

Majority Voter ◽

Garbage Output ◽

Reversible Logic Gates ◽

Novel Design

Quantum-dot cellular automata (QCA) suggest an emerging computing paradigm for nanotechnology. The QCA offers novel approach in electronics for information processing and communication. QCA have recently become the focus of interest in the field of low power nanocomputing and nanotechnology. The fundamental logic elements of this technology are the majority voter (MV) and the inverter (INV). This paper presents a novel design with less garbage output and minimum quantum cost in nanotechnology. In the paper we show how to create multipurpose reversible gates. By development of suitable gates in logic circuits as an example, we can combine MFA and HS in one design using CMVMIN gate. We offer CMVMIN gate implementations to be used in multipurpose circuit. We can produce concurrent half adder/subtractor and one bit comparator in one design using reversible logic gates and CMVMIN gates. Also, a 2×4 decoder from recent architecture has been shown independently. We investigate the result of the proposed design using truth table. A significant improvement in quality of the calculated parameters and variety of required outputs has been achieved.

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Novel design of Morlet wavelet neural network for solving second order Lane–Emden equation

Mathematics and Computers in Simulation ◽

10.1016/j.matcom.2020.01.005 ◽

2020 ◽

Vol 172 ◽

pp. 1-14 ◽

Cited By ~ 23

Author(s):

Zulqurnain Sabir ◽

Hafiz Abdul Wahab ◽

Muhammad Umar ◽

Mehmet Giyas Sakar ◽

Muhammad Asif Zahoor Raja

Keyword(s):

Neural Network ◽

Morlet Wavelet ◽

Wavelet Neural Network ◽

Second Order ◽

Emden Equation ◽

Novel Design

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Analytical and Approximate Solutions of a Novel Nervous Stomach Mathematical Model

Discrete Dynamics in Nature and Society ◽

10.1155/2020/5063271 ◽

2020 ◽

Vol 2020 ◽

pp. 1-9 ◽

Cited By ~ 3

Author(s):

Yolanda Guerrero Sánchez ◽

Zulqurnain Sabir ◽

Hatıra Günerhan ◽

Haci Mehmet Baskonus

Keyword(s):

Mathematical Model ◽

Numerical Simulations ◽

Death Rate ◽

Approximate Solutions ◽

Mathematical Form ◽

Nonlinear Mathematical Model ◽

Transformation Technique ◽

Differential Transformation ◽

Sleep Factor

The stomach is usually considered as a hollow muscular sac, which initiates the second segment of digestion. It is the most sophisticated endocrine structure having unique biochemistry, physiology, microbiology, and immunology. The pivotal aim of the present study is to propose the nonlinear mathematical model of the nervous stomach system based on three compartments namely, tension (T), food (F), and medicine (M). The detailed description of each compartment is provided along with the mathematical form and different rates/factors, such as sleep factor, food rate, tension rate, medicine term, and death rate. The solution of the designed model is presented numerically by using the well-known differential transformation technique. The behavior of the obtained solution has been captured with respect to time as well as presentations of the numerical simulations.

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Evolutionary Integrated Heuristic with Gudermannian Neural Networks for Second Kind of Lane–Emden Nonlinear Singular Models

Applied Sciences ◽

10.3390/app11114725 ◽

2021 ◽

Vol 11 (11) ◽

pp. 4725

Author(s):

Kashif Nisar ◽

Zulqurnain Sabir ◽

Muhammad Asif Zahoor Raja ◽

Ag. Asri Ag. Ibrahim ◽

Joel J. P. C. Rodrigues ◽

...

Keyword(s):

Artificial Intelligence ◽

Neural Networks ◽

Active Set ◽

Active Set Method ◽

Hybrid Heuristics ◽

Hidden Layer ◽

The Stability ◽

Intelligence Approach ◽

Artificial Intelligence Approach ◽

Search Capability

In this work, a new heuristic computing design is presented with an artificial intelligence approach to exploit the models with feed-forward (FF) Gudermannian neural networks (GNN) accomplished with global search capability of genetic algorithms (GA) combined with local convergence aptitude of active-set method (ASM), i.e., FF-GNN-GAASM to solve the second kind of Lane–Emden nonlinear singular models (LE-NSM). The proposed method based on the computing intelligent Gudermannian kernel is incorporated with the hidden layer configuration of FF-GNN models of differential operatives of the LE-NSM, which are arbitrarily associated with presenting an error-based objective function that is used to optimize by the hybrid heuristics of GAASM. Three LE-NSM-based examples are numerically solved to authenticate the effectiveness, accurateness, and efficiency of the suggested FF-GNN-GAASM. The reliability of the scheme via statistical valuations is verified in order to authenticate the stability, accuracy, and convergence.

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Designing of Morlet wavelet as a neural network for a novel prevention category in the HIV system

International Journal of Biomathematics ◽

10.1142/s1793524522500127 ◽

2021 ◽

Author(s):

Zulqurnain Sabir ◽

Muhammad Umar ◽

Muhammad Asif Zahoor Raja ◽

Haci Mehmet Baskonus ◽

Wei Gao

Keyword(s):

Neural Network ◽

Genetic Algorithm ◽

Mathematical Model ◽

Initial Conditions ◽

Error Function ◽

Morlet Wavelet ◽

Interior Point Algorithm ◽

The Novel ◽

Numerical Performance ◽

Independent Trials

The aim of this work is to present a design of Morlet wavelet neural network (MWNN) for solving a novel prevention category (P) in the HIV system, known as HIPV mathematical model. The numerical performance of the novel HIPV mathematical model will be observed by exploiting the MWNN that works through the optimization procedures of global/local via “genetic algorithm (GA)” and local search “interior-point algorithm (IPA)”, i.e. MWNN-GA-IPA. An error function using the differential HIPV mathematical model and its initial conditions is presented and optimized by the MWNN-GA-IPA. The obtained results have been compared with the Adams method to check the competence of the MWNN-GA-IPA. For the reliability and stability of the scheme, the performance using different statistical operators has been performed based on the multiple independent trials to solve the novel HIPV mathematical model.

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