Browsing by Author "Khadeejah James Audu"

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A Backward Diffrention Formula For Third-Order Inttial or Boundary Values Problems Using Collocation Method
(Islamic Azad University,Rasht ', Iran, 2021-09-19) AbdGafar Tunde Tiamiyu; Abosede Temilade Cole; Khadeejah James Audu
We propose a new self-starting sixth-order hybrid block linear multistep method using backward differentiation formula for direct solution of third-order differential equations with either initial conditions or boundary conditions. The method used collocation and interpolation techniques with three off-step points and five-step points, choosing power series as the basis function. The convergence of the method is established, and three numerical experiments of initial and boundary value problems are used to demonstrate the efficiency of the proposed method. The numerical results in Tables and Figures show the efficiency of the method. Furthermore, the numerical method outperformed the results from existing literature in terms of accuracy as evident in the results of absolute errors produced
A COMPARATIVE ANALYSIS OF TWO SEMI ANALYTIC APPROACHES IN SOLVING SYSTEMS OF FIRST-ORDER DIFFERENTIAL EQUATIONS
(Mehmet Akif Ersoy University, Turkey., 2024-06-29) Khadeejah James Audu; Onifade Babatunde
The resolution of systems of first-order ordinary differential equations (ODEs) is a critical endeavor with extensive applications in various scientific and engineering fields. This study presents a rigorous comparative assessment of two semi-analytic methodologies: the Variational Iterative Method (VIM) and the New Iterative Method (NIM). Addressing a significant research gap, our investigation explores the relative merits and demerits of these approaches. We provide a comprehensive examination of VIM, a well-established method, alongside NIM, a relatively less explored approach, to identify their comparative strengths and limitations. Furthermore, the study enriches existing knowledge in numerical methods for ODEs by highlighting essential performance characteristics such as convergence properties, computational efficiency, and accuracy across a diverse array of ODE systems. Through meticulous numerical experimentation, we uncover practical insights into the efficacy of VIM and NIM, bridging a critical knowledge gap in the field of numerical ODE solvers. Our findings demonstrate VIM as the more effective method, thereby enhancing the understanding of semi-analytic approaches for solving ODE systems and providing valuable guidance for practitioners and researchers in selecting the most appropriate method for their specific applications
A Comparative Study Of Two Iterative Techniques For Systems Of Linear Algebraic Equations
(Academic Staff Union of Universities, Nigeria, 2021-12-20) Khadeejah James Audu
This study compares numerically two iterative methods for solving systems of linear algebraic equations: the Symmetric Accelerated Overrelaxation technique and the Symmetric Successive Overrelaxation method. Four numerical problems are applied to analyze and compare the convergence speeds of the two approaches. On the basis of performance metrics including spectral radius, convergence time, accuracy, and number of iterations required to converge, the numerical results demonstrate that the Symmetric Accelerated Overrelaxation approach needed less computing time, a smaller spectral radius, and fewer iterations than the Symmetric Successive Overrelaxation approach. This demonstrates that the Symmetric Accelerated Overrelaxation is superior to the Symmetric Successive Overrelaxation. Researchers and numerical analysts can benefit from the findings of this study; it will help them comprehend iteration techniques and adopt an appropriate or more efficient iterative strategy for solving systems of linear algebraic equations.
A groundwater-based irrigation modeling system that optimizing water use efficiency and ensuring long-term sustainability of groundwater resources.
(Maths Model Research Group, FUT, Minna, Nigeria, 2025-03-20) Y. Y. Alheri; N. Nyor; Khadeejah James Audu
A THIRD REFINEMENT OF JACOBI METHOD FOR SOLUTIONS TO SYSTEM OF LINEAR EQUATIONS
(Federal University, Dutsin Ma, Nigeria, 2023-10-15) Khadeejah James Audu; James Nkereuwem Essien; Abraham Baba Zhiri; Aliyu Rasheed Taiwo
Solving linear systems of equations stands as one of the fundamental challenges in linear algebra, given their prevalence across various fields. The demand for an efficient and rapid method capable of addressing diverse linear systems remains evident. In scenarios involving large and sparse systems, iterative techniques come into play to deliver solutions. This research paper contributes by introducing a refinement to the existing Jacobi method, referred to as the "Third Refinement of Jacobi Method." This novel iterative approach exhibits its validity when applied to coefficient matrices exhibiting characteristics such as symmetry, positive definiteness, strict diagonal dominance, and 𝑀 -matrix properties. Importantly, the proposed method significantly reduces the spectral radius, thereby curtailing the number of iterations and substantially enhancing the rate of convergence. Numerical experiments were conducted to assess its performance against the original Jacobi method, the second refinement of Jacobi, and the Gauss-Seidel method. The outcomes underscore the "Third Refinement of Jacobi" method's potential to enhance the efficiency of linear system solving, thereby making it a valuable addition to the toolkit of numerical methodologies in scientific and engineering domains.
Advancements in Solving Higher-Order Ordinary Differential Equations via the Variational Iterative Method.
(Akdeniz University, Turkey, 2025-12-30) Khadeejah James Audu; Michael Ogbole Ogwuche; Sıkırulaı Abolaji Akande; Yahaya Yusuph Amuda
This study presents advancements in solving higher-order ordinary differential equations (ODEs) using the Variational Iterative Method (VIM) and compares its performance with the New Iteration Method (NIM) and Adomian Decomposition Method (ADM). ODEs are critical in modeling the rate of change in various systems over time, and many do not have exact solutions, necessitating the use of numerical methods to obtain approximate results. While several iterative methods exist, a detailed comparison of VIM with other techniques, particularly for higher-order ODEs, is still lacking. This research focuses on understanding the principles and methodology of VIM and applying it to solve higher-order linear and nonlinear ODEs. The study evaluates the accuracy, convergence rate, and computational efficiency of VIM compared to NIM and ADM through the solution of third, fourth, and fifth-order differential problems. The results show that VIM outperforms NIM and ADM, with faster convergence and higher efficiency. Error analysis in Figures 1, 2, and 3 highlights the strengths and limitations of each method, providing valuable insights for researchers and practitioners in selecting the most appropriate technique for solving higher-order ODEs. These findings advance the development of iterative methods in numerical analysis and contribute to progress in the field of differential equations.
An Investigative Comparison of Higher-Order Runge-Kutta Techniques for Resolving First-Order Differential Equations
(Fırat University, Turkey, 2025-07-14) Khadeejah James Audu; Victor James Udoh; Jamiu Garba
In the context of solving first-order ordinary differential equations (ODEs), this paper thoroughly compares various higher-order Runge-Kutta methods. Reviewing the effectiveness, precision, and practicality of several Runge-Kutta schemes and highlighting their usage in numerical approximation is the main goal of the research. The study explores traditional approaches, including the fifth-order, six-stage Runge-Kutta (RK56), the sixth-order, seven-stage Runge-Kutta (RK67), and the seventh-order, nine-stage Runge-Kutta (RK79), with the goal of offering a comprehensive comprehension of their individual advantages and disadvantages. In order to help academics and practitioners choose the best approach based on the features of the problem, comparative benchmarks are constructed, utilizing both theoretical underpinnings and real-world implementations. Robustness evaluations and sensitivity analysis complement the comparison research by illuminating how flexible these techniques are in various context. The results of this study provide important new understandings of how higherorder Runge-Kutta methods function and provide a thorough manual for applying them to solve first-order differential problems in a variety of scientific and engineering fields. The study’s examination of three higher order Runge-Kutta algorithms reveals that the RK56 is more effective at solving first order ODEs
Analysis of Fire Outbreak in Coupled Atmospheric-Wildfire.
(Ibrahim Badamasi Babangida University, Lapai, Nigeria, 2021-06-20) Zhiri, A. B.; Olayiwola, R. O.; Khadeejah James Audu; Adeloye, T. O.; Gupa, M. I
Forest fire outbreak has become alarming day by day as it is a common occurrence in most parts of the world and it cause a lot of havoc to biodiversity as well as to the local ecology. In this paper, a partial differential equations (PDE) governing wildland fire outbreak is presented. We obtained the approximate analytical solution of the model using perturbation method, direct integration and eigenfunction expansion technique, which clearly depicts the influence of the parameters involved in the system. The effect of change in parameters such as Radiation number, Peclet energy number, Peclet mass number, and Equilibrium wind velocity on oxygen concentration are shown graphically and discussed. The results obtained revealed that as Radiation number and Peclet energy number increases, oxygen concentration depreciates. While increasing Peclet mass number, and Equilibrium wind velocity enhanced oxygen concentration.
Application of Backward Differentiation Formula on Fourth-Order Differential Equations.
(Universiti Tun Hussein Onn Malaysia Publisher’s Office, Malaysia, 2022-12-30) Khadeejah James Audu; Jamiu Garba; Abdgafar Tunde Tiamiyu; Blessing Ashiodime Thomas
Higher order ordinary differential equations are typically encountered in engineering, physical science, biological sciences, and numerous other fields. The analytical solution of the majority of engineering problems involving higher-order ordinary differential equations is not a simple task. Various numerical techniques have been proposed for higher-order initial value problems (IVP), but a higher degree of precision is still required. In this paper, we propose a novel two-step backward differentiation formula in the class of linear multistep schemes with a higher order of accuracy for solving ordinary differential equations of the fourth order. The proposed method was created by combining interpolation and collocation techniques with the use of power series as the basis function at some grid and off-grid locations to generate a hybrid continuous two-step technique. The method's fundamental properties, such as order, zero stability, error constant, consistency, and convergence, were explored, and the analysis showed that it is zero stable, consistent and convergent. The developed method is suitable for numerically integrating linear and nonlinear differential equations of the fourth order. Four Numerical tests are presented to demonstrate the efficiency and accuracy of the proposed scheme in comparison to some existing block methods. Based on what has been observed, the numerical results indicate that the proposed scheme is a superior method for estimating fourth-order problems than the method previously employed, confirming its convergence.
Application of Grey-Markov Model for Forecasting Nigeria Annual Rice Production
(African Journal Online (AJOL), South Africa, 2021-11-21) Lawal Adamu; Didigwu, N. E.; Saidu, D. Y; Sadiq, S. L.; Khadeejah James Audu
In this paper, Grey system model (GM(1,1)) and Grey-Markov model that forecast Nigeria annual Rice production have been presented. The data used in the research were collected from the archive of Central Bank of Nigeria for a period of Six years (2010-2015). The fitted models showed high level of accuracy. Hence, the models can be used for food security plans of the nation.
Application of Hidden Markov Model in Yam Yield Forecasting.
(African Journal Online (AJOL), Soutrh Africa, 2022-06-06) 11. Lawal Adamu; Saidu Daudu Yakubu; Didigwu Ndidiamaka Edith; Abdullahi Abubakar; Khadeejah James Audu; Isaac Adaji.
Providing the government and farmers with reliable and dependable information about crop yields before each growing season begins is the thrust of this research. A four-state stochastic model was formulated using the principle of Markov, each state of the model has three possible observations. The model is designed to make a forecast of yam yield in the next and subsequent growing seasons given the yam yield in the present growing season. The parameters of the model were estimated from the yam yield data of Niger state, Nigeria for the period of sixteen years(2001-2016). After which, the model was trained using Baum-Welch algorithm to attend maximum likelihood. A short time validity test conduct on the model showed good performance. Both the validity test and the future forecast shows prevalence of High yam yield, this attest to the reality on the ground, that Niger State is one of the largest producers of yam in Nigeria. The general performance of the model, showed that it is reliable therefore, the results from the model could serve as a guide to the yam farmers and the government to plan strategies for high yam production in the region.
Application of Singular Value Decomposition technique for compressing images
(Bauchi State University, Gadau, Nigeria, 2022-08-19) Khadeejah James Audu
Image processing is becoming increasingly important as imaging technology has advanced. A storage constraint might occur even when image quality is an influential factor. This means finding a way to reduce the volume of data while still retaining quality, since compactable systems and minimal space are more desirable in the current computing field. An image compression technique that is frequently used is singular value decomposition (SVD). SVD is a challenging and promising way to loosely compress images, given how many people use images now and how many different kinds of media there are. SVD can be employed to compress digital images by approximating the matrices that generate such images, thereby saving memory while quality is affected negligibly. The technique is a great tool for lowering image dimensions. However, SVD on a large dataset might be expensive and time-consuming. The current study focuses on its improvement and implements the proposed technique in a Python environment. We illustrate the concept of SVD, apply its technique to compress an image through the use of an improved SVD process, and further compare it with some existing techniques. The proposed technique was used to test and evaluate the compression of images under various r-terms, and the singular value characteristics were incorporated into image processing. By utilization of the proposed SVD technique, it was possible to compress a large image of dimension 4928 x 3264 pixels into a reduced 342 x 231 pixels with fair quality. The result has led to better image compression in terms of size, processing time, and errors.
Assessment of Numerical Performance of Some Runge-Kutta Methods and New Iteration Method on First Order Differential Problems
(Federal University, Dutse, Nigeria, 2023-12-10) Khadeejah James Audu; Aliyu Rasheed Taiwo; Abdulganiyu Alabi Soliu
This research focuses on the assessment of the numerical performance of some Runge-Kutta methods and New Iteration Method “NIM” for solving first-order differential problems. The assessment is conducted through extensive numerical experiments and comparative analyses. Accuracy, efficiency, and stability are among the key factors considered in evaluating the performance of the methods. A range of first-order differential problems with diverse characteristics and complexity levels is employed to thoroughly examine the methods' capabilities and limitations. The numerical investigation that is defined in the study as well as the results that are stated in the Tables, demonstrates that all the approaches produce extremely accurate results. However, the “NIM” was shown to be the most effective of the three methods used in this study. Conclusively, the “NIM” should be employed to solve first-order nonlinear and linear ordinary differential equations in place of Runge-Kutta Fourth order method (RK4M) and Butcher Runge-Kutta Fifth order method (BRK5M). In addition, BRK5M is more applicable and efficient than RK4M when solving first order ordinary differential problems.
BLOCK METHOD APPROACH FOR COMPUTATION OF ERRORS OF SOME ADAMS CLASS OF METHODS
(Association of Nigerian Journal of Physics, 2022-12-12) Yahaya, Y. A.; Odeyemi, A. O.; Khadeejah James Audu
Traditionally, the error and order constant of block linear multistep methods were analyzed by examining each block members separately. This paper proposes a block-by-block analysis of the schemes as they appear for implementation. Specifically, cases when k= 2, 3, 4, and 5 for Adams Moulton (implicit) are reformulated as continuous schemes in order to generate a sufficient number of schemes required for the methods to be self-starting. The derivation was accomplished through the continuous collocation technique utilizing power series as the basis function, and the property of order and error constants is examined across the entire block for each case of the considered step number. The findings of the study generated error constants in block form for Adams Bashforth and Adams Moulton procedures at steps 2, 3, 4, 5 k  . Furthermore, the relevance of the study demonstrates that calculating all members' error constants at once, reduces the amount of time necessary to run the analysis. The new approach, for examining the order and error constants of a block linear multistep method, is highly recommended for application in solving real-world problems, modelled as ordinary and partial differential equations
Comparative Numerical Evaluation of Some Runge-Kutta Methods for Solving First Order Systems of ODEs
(Toros University Publishing house, Turkey, 2025-12-12) Khadeejah James Audu; Tunde Adekunle Abubakar; Yahaya Yusuph Amuda; James Essien Nkereuwem
In this study, a comparative analysis of two Runge-Kutta methods; fourth-order Runge-Kutta method and Butcher’s Fifth Order Runge-Kutta method are presented and used to solve systems of first-order linear Ordinary Differential Equations (ODEs). The main interest of this work is to test the accuracy, convergence rate and computational efficiency of these methods by using different numerical problems of ODEs. Empirical conclusions are drawn after close observation of the results presented by the two methods, which further highlights their limitations and enabling researchers to make informed decisions in choosing the appropriate technique for specific systems of ODEs problems.
Computational Algorithm for Volterra Integral Solutions via Variational. Iterative Method
(Paper Presentation at University of Lagos, Nigeria, 2023-08-28) Khadeejah James Audu
The Volterra Integral Equations (VIE) are a class of mathematical equations that find applications in various fields, including physics, engineering, and biology. Solving VIEs analytically is often challenging, and researchers have turned to numerical methods for obtaining approximate solutions. In this research, we propose a computational algorithm based on the Variational Iterative Method (VIM) to efficiently and accurately solve VIEs. By incorporating this method into the computational algorithm, we aim to improve the accuracy and convergence rate of the solutions. The performance of our algorithm was evaluated through extensive numerical experiments on various types of VIEs. The results demonstrate the effectiveness of the VIM approach in terms of accuracy, convergence rate, and computational efficiency. In conclusion, the proposed computational algorithm based on VIM presents a valuable contribution to the field of solving VIEs. It offers an efficient and accurate approach for obtaining approximate solutions, enabling researchers and practitioners to tackle complex problems that rely on VIEs. The algorithm's versatility and robustness make it a promising tool for a wide range of applications, including physics, engineering, and biology.
CONTINUOUS FORMULATION OF HYBRID BLOCK MILNE TECHNIQUE FOR SYSTEM OF ORDINARY DIFFERENTIAL EQUATIONS
(Mathematical Association of Nigeria (MAN), 2022-12-13) Khadeejah James Audu; Y. A. Yahaya,; J. Garba; A. T. Cole; F. U. Tafida
In most scientific and engineering problems, ordinary differential equations cannot be solved by analytic methods. Consequently, numerical approaches are frequently required. A block hybrid Milne technique was formulated in this paper in order to develop a suitable algorithm for the numerical solution of ordinary differential equations. Utilizing power series as the basis function, the proposed method is developed. The developed algorithm is used to solve systems of linear and nonlinear differential equations, and it has proven to be an efficient numerical method for avoiding timeconsuming computation and simplifying differential equations. The fundamental numerical properties are examined, and the results demonstrate that it is zero-stable and consistent, which ensures convergence. In addition, by comparing the approximate solutions to the exact solutions, we demonstrate that the approximate solutions converge to the exact solutions. The results demonstrate that the developed algorithm for solving systems of ordinary differential equations is straightforward, efficient, and faster than the analytical method.
Convergence of Triple Accelerated Over-Relaxation (TAOR) Method for M-Matrix Linear Systems
(Islamic Azad University, Rasht, Iran, 2021-09-19) Khadeejah James Audu; Yusuph Amuda Yahaya; Rufus Kayode Adeboye; Usman Yusuf Abubakar
In this paper, we propose some necessary conditions for convergence of Triple Accelerated Over-Relaxation (TAOR) method with respect to 𝑀 − coefficient matrices. The theoretical approach for the proofs is analyzed through standard procedures in the literature. Some numerical experiments are performed to show the efficiency of our approach, and the results obtained compared favourably with those obtained through the existing methods in terms of spectral radius of their iteration matrices
Effects of Relaxation Times from Bloch Equations on Age-Related Change in White and Grey Matter
(University of Lagos, Nigeria, 2024-02-20) Yusuf, S. I.; D. O. Olaoye; M. O. Dada; A. Saba; Khadeejah James Audu; J. A. Ibrahim; A. O. Jatto
This research work presented the analytical method of using T1 and T2 relaxation rates of white matter and grey matter to distinguish the passage of time on human organs. A time dependent model equation evolved from the Bloch Nuclear Magnetic Resonance equation was solved under the influence of the radio frequency magnetic field [rfB1(x, t) ̸= 0] and in the absence of radio frequency magnetic field [rfB1(x, t) = 0]. The general solution was considered in three cases. Analysis of the solutions obtained revealed that the rate of decrease of the white matter was faster than that of the grey matter. Between 100 and 400 seconds the difference is more noticeable.
Enhancing Linear System Solving Through Third Refinement of Successive and Accelerated Over-Relaxation Methods
(Çankaya University, Turkey, 2024-03-27) Khadeejah James Audu; Malik Oniwinde Oyetunji; James Essien Nkereuwem
One of the primary difficulties in linear algebra, considering its widespread application in many different domains, is solving linear system of equations. It is nevertheless apparent that there is a need for a quick, effective approach that can handle a variety of linear systems. In the realm of large and sparse systems, iterative methods play a crucial role in finding solutions. This research paper makes a significant contribution by introducing an enhancement to the current methodology Successive and Accelerated Over Relaxation methods, referred to as the "Third Refinement of Successive and Accelerated Over Relaxation Methods." This new iterative approach demonstrates its effectiveness when applied to coefficient matrices exhibiting properties such as 𝑀- matrix, irreducible diagonal dominance, positive definiteness and symmetry characteristics. Significantly, the proposed method substantially reduces the spectral radius, resulting in fewer iterations and notably enhancing the convergence rate. Numerical experiments were conducted to evaluate its performance compared to existing second refinement of Successive and Accelerated Over Relaxation methods. The outcomes underscore the "Third Refinement of Successive and Accelerated Over Relaxation" methods potentially to boost the efficiency of solving linear systems, thus rendering it a valuable asset within the arsenal of numerical methodologies utilized in scientific and engineering realms