This study deals with the numerical investigation of Jeffery-Hamel flow and heat transfer in Eyring-Powell fluid in the presence of an outer magnetic field by using Haar wavelet method. Jeffery-Hamel flows occur in various practical situations involving flow between two non-parallel walls. Applications of such fluids in biological and industrial sciences brought a great concern to the investigation of flow characteristics in converging and diverging channels. A suitable similarity transformation is applied to transform the nonlinear coupled partial differential equations (PDEs) into nonlinear coupled ordinary differential equations (ODEs), which govern the momentum and heat transfer properties of the fluid. Due to the high nonlinearity of resulting coupled ODEs, the exact solution is unlikely. Thus, the solution is approximated using a numerical scheme based on Haar wavelets and the results are verified by comparing with 4th order Runge-Kutta results.

The actual motivation of this paper is to develop a functional link between artificial neural network (ANN) with Legendre polynomials and simulated annealing termed as Legendre simulated annealing neural network (LSANN). To demonstrate the applicability, it is employed to study the nonlinear Lane-Emden singular initial value problem that governs the polytropic and isothermal gas spheres. In LSANN, minimization of error is performed by simulated annealing method while Legendre polynomials are used in hidden layer to control the singularity problem. Many illustrative examples of Lane-Emden type are discussed and results are compared with the formerly used algorithms. As well as with accuracy of results and tranquil implementation it provides the numerical solution over the entire finite domain.

This chapter offers a numerical simulation of fractional differential equations by utilizing Chebyshev-simulated annealing neural network (ChSANN) and Legendre-simulated annealing neural network (LSANN). The use of Chebyshev and Legendre polynomials with simulated annealing reduces the mean square error and leads to more accurate numerical approximation. The comparison of proposed methods with previous methods confirms the accuracy of ChSANN and LSANN.

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To enrich any model and its dynamics introduction of delay is useful, that models a precise description of real-life phenomena. Differential equations in which current time derivatives count on the solution and its derivatives at a prior time are known as delay differential equations (DDEs). In this study, we are introducing new techniques for finding the numerical solution of fractional delay differential equations (FDDEs) based on the application of neural minimization (NM) by utilizing Chebyshev simulated annealing neural network (ChSANN) and Legendre simulated annealing neural network (LSANN). The main purpose of using Chebyshev and Legendre polynomials, along with simulated annealing (SA), is to reduce mean square error (MSE) that leads to more accurate numerical approximations. This study provides the application of ChSANN and LSANN for solving DDEs and FDDEs. Proposed schemes can be effortlessly executed by using Mathematica or MATLAB software to get explicit solutions. Computational outcomes are depicted, for various numerical experiments, numerically and graphically with error analysis to demonstrate the accuracy and efficiency of the methods.

Communication with a hearing-impaired individual is a big challenge for a normal person. Hearingimpaired people uses hand gesture language (sign language) to communicate with each other, which is not easy to understand by a normal person because he/she is not trained to understand sign language. This communication gap between a hearing-impaired and a normal person created big problem for hearing-impaired individuals during their shopping, hospitalization, at their schools and homes. Especially in case of emergency, it is very difficult to understand the statement of a hearing-impaired one's who uses sign language. In the last few years researchers and developers from all over the world presented different ideas and works to solve this problem but no such solution is available to resolve this issue and can create two-way communication between hearing-impaired and normal persons. This paper presented a detail description about a two-way communication system based on Pakistan Sign Language (PSL). This duplex system is developed through conversion from the text in simple English into hand gestures and vice versa. However, conversion from hand gestures is available not only in text but also with voice providing more convenience to normal person. Main objective is to facilitate a large population and making hearingimpaired persons, the vital part of our civilization. A normal person can enter the text (sentence) in application, after the checking of spelling and grammar, the text is divided into tokens and sub-tokens. A token is a gesture against each word of the text while sub-tokens are the gestures of each character of the words. The combination of tokens created the gestures of text. On the other hand when gestures were input in to the application, using image processing technique, the nature of hand gesture were recognized and converted into corresponding text or voice.

In this article, Legendre simulated annealing, neural network (LSANN) is designed for fuzzy fractional order differential equations, which is employed on fractional fuzzy initial value problem (FFIVP) with triangular condition. Here, Legendre polynomials are used to modify the structure of neural networks with a Taylor series approximation of the tangent hyperbolic as activation function while the network adaptive coefficients are trained in the procedure of simulated annealing to optimize the residual error. The computational results are depicted in terms of numerical values to compare them with previous results.

Abstract:The motivation of this paper is to study the fourth order Emden-Fowler equations with initial values by Haar wavelet collocation method (HWCM). In this methodology, differential equations are transformed into a system of linear or nonlinear equations that leads to the value of Haar coefficients and later the solution can be obtained on the entire domain (0, 1]. The fourth order nonlinear test examples are solved at different Haar levels to analyze the accuracy of results. The simplicity and effectiveness of the method made it more attractive than non-perturbative methods found in literature.