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Journal articles on the topic 'Predictor corrector'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Wang, Tao, Hongbo Zhang, and Guojian Tang. "Predictor-corrector guidance for entry vehicle based on fuzzy logic." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 233, no. 2 (2017): 472–82. http://dx.doi.org/10.1177/0954410017737574.

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With the development of aerospace industry, the guidance system of an entry vehicle will be more robust, reliable and autonomous in the future. Based on fuzzy logic, the paper designs a predictor-corrector guidance law. The trajectory prediction is realized by numerical integration. The correction system is based on two fuzzy controllers, which correct the longitudinal motion and lateral motion synergistically. The error of flight range is eliminated by correcting the magnitude of bank angle. The altitude error is eliminated by correcting the attack angle. The lateral error is eliminated by re

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2

Zhong, Baojiang, Kai-Kuang Ma, and Zhifang Lu. "Predictor-corrector image interpolation." Journal of Visual Communication and Image Representation 61 (May 2019): 50–60. http://dx.doi.org/10.1016/j.jvcir.2019.03.018.

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3

van der Houwen, P. J., B. P. Sommeijer, and J. J. B. de Swart. "Parallel predictor-corrector methods." Journal of Computational and Applied Mathematics 66, no. 1-2 (1996): 53–71. http://dx.doi.org/10.1016/0377-0427(95)00158-1.

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4

Butcher, John C., and Pavla Sehnalová. "Predictor–corrector Obreshkov pairs." Computing 95, no. 5 (2013): 355–71. http://dx.doi.org/10.1007/s00607-012-0258-0.

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5

Shang, Dequan, and Xiaobin Guo. "Adams Predictor-Corrector Systems for Solving Fuzzy Differential Equations." Mathematical Problems in Engineering 2013 (2013): 1–12. http://dx.doi.org/10.1155/2013/312328.

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A predictor-corrector algorithm and an improved predictor-corrector (IPC) algorithm based on Adams method are proposed to solve first-order differential equations with fuzzy initial condition. These algorithms are generated by updating the Adams predictor-corrector method and their convergence is also analyzed. Finally, the proposed methods are illustrated by solving an example.

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6

JOSHI, MARK, and ALEXANDER WIGUNA. "ACCELERATING PATHWISE GREEKS IN THE LIBOR MARKET MODEL." International Journal of Theoretical and Applied Finance 15, no. 02 (2012): 1250012. http://dx.doi.org/10.1142/s0219024912500124.

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In the framework of the displaced-diffusion LIBOR market model, we derive the pathwise adjoint method for the iterative predictor-corrector and one of the Glasserman–Zhao drift approximations in the spot measure. This allows us to compute fast deltas and vegas under these schemes. We compare the discretisation bias obtained when computing Greeks with these methods to those obtained under the log-Euler and predictor-corrector approximations by performing tests with interest rate caplets and cancellable receiver swaps. The two predictor-corrector type methods were the most accurate by far. In pa

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Dong, Ning, Jicheng Jin, and Bo Yu. "Convergence Rates of a Class of Predictor-Corrector Iterations for the Nonsymmetric Algebraic Riccati Equation Arising in Transport Theory." Advances in Applied Mathematics and Mechanics 9, no. 4 (2017): 944–63. http://dx.doi.org/10.4208/aamm.2015.m1277.

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AbstractIn this paper, we analyse the convergence rates of several different predictor-corrector iterations for computing the minimal positive solution of the nonsymmetric algebraic Riccati equation arising in transport theory. We have shown theoretically that the new predictor-corrector iteration given in [Numer. Linear Algebra Appl., 21 (2014), pp. 761–780] will converge no faster than the simple predictor-corrector iteration and the nonlinear block Jacobi predictor-corrector iteration. Moreover the last two have the same asymptotic convergence rate with the nonlinear block Gauss-Seidel iter

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8

Yang, Chao, Duo Li, Tao Zhu, and Shoune Xiao. "Assessment of numerical integration algorithms for nonlinear vibration of railway vehicles." Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 231, no. 6 (2016): 729–39. http://dx.doi.org/10.1177/0954409716640825.

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The primary purpose of this paper was to choose appropriate time integration methods for the simulation of nonlinear railway vehicle systems. The nonlinear elements existing in railway vehicle systems were summarized, and the relevant mathematical expressions were provided. A newly developed integration method, which is the corrected explicit method of double time steps, was implemented in five typical nonlinear examples of nonlinear railway vehicle systems. The Newmark method, the Wilson-θ method, the Runge–Kutta method, the predictor-corrector Adams method, the Zhai method, and the precise i

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9

Kayode, S. J., F. O. Obarhua, and F. C. Ogedengbe. "Development and Implementation of Four-Step Predictor-Corrector Method with an Improvement Strategy for Fourth-Order Ordinary Differential Equations with Applications." Scholars Journal of Physics, Mathematics and Statistics 12, no. 04 (2025): 114–29. https://doi.org/10.36347/sjpms.2025.v12i04.005.

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This article focuses on the development, theoretical analysis, and implementation of a four-level predictor-corrector method with an improved strategy for solving fourth-order ordinary differential equations using initial conditions. When developing the method, Chebyshev polynomials of the first kind were adopted as the basis functions for solving the IVP. Chebyshev polynomials of the first kind were interpolated at some selected grid and off-grid points, and the fourth derivative of the approximate solution was collocated at all grid and off-grid points. The methods was derived and implemente

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10

Subhashini and B. Srividhya. "Comparison of Several Numerical Algorithms with the use of Predictor and Corrector for solving ode." International Journal of Trend in Scientific Research and Development 3, no. 6 (2019): 1057–60. https://doi.org/10.5281/zenodo.3589313.

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In this paper, we introduce various numerical methods for the solutions of ordinary differential equations and its application. We consider the Taylor series, Runge Kutta, Euler's methods problem to solve the Adam's Predictor, Corrector and Milne's Predictor, Corrector to get the exact solution and the approximate solution. Subhashini | Srividhya. B "Comparison of Several Numerical Algorithms with the use of Predictor and Corrector for solving ode" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issu

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11

Xue, Songbai, and Ping Lu. "Constrained Predictor-Corrector Entry Guidance." Journal of Guidance, Control, and Dynamics 33, no. 4 (2010): 1273–81. http://dx.doi.org/10.2514/1.49557.

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12

Iavernaro, F., and F. Mazzia. "Parallel implicit predictor corrector methods." Applied Numerical Mathematics 42, no. 1-3 (2002): 235–50. http://dx.doi.org/10.1016/s0168-9274(01)00153-2.

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13

Marciniak, Andrzej, Malgorzata A. Jankowska, and Tomasz Hoffmann. "On interval predictor-corrector methods." Numerical Algorithms 75, no. 3 (2016): 777–808. http://dx.doi.org/10.1007/s11075-016-0220-x.

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14

de Swart, J. J. B. "Efficient parallel predictor-corrector methods." Applied Numerical Mathematics 18, no. 1-3 (1995): 387–96. http://dx.doi.org/10.1016/0168-9274(95)00061-x.

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15

Lahmam, H., J. M. Cadou, H. Zahrouni, N. Damil, and M. Potier-Ferry. "High-order predictor-corrector algorithms." International Journal for Numerical Methods in Engineering 55, no. 6 (2002): 685–704. http://dx.doi.org/10.1002/nme.524.

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16

Chrysinas, Panagiotis, Changyou Chen, and Rudiyanto Gunawan. "CrossTx: Cross-Cell-Line Transcriptomic Signature Predictions." Processes 12, no. 2 (2024): 332. http://dx.doi.org/10.3390/pr12020332.

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Predicting the cell response to drugs is central to drug discovery, drug repurposing, and personalized medicine. To this end, large datasets of drug signatures have been curated, most notably the Connectivity Map (CMap). A multitude of in silico approaches have also been formulated, but strategies for predicting drug signatures in unseen cells—cell lines not in the reference datasets—are still lacking. In this work, we developed a simple-yet-efficacious computational strategy, called CrossTx, for predicting the drug transcriptomic signatures of an unseen target cell line using drug transcripto

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17

Oghonyon, Jimevwo Godwin, Matthew Etinosa Egharevba, and Ogbu Famous Imaga. "The Extended Block Predictor-Block Corrector Method for Computing Fuzzy Differential Equations." WSEAS TRANSACTIONS ON MATHEMATICS 22 (September 19, 2022): 1–12. http://dx.doi.org/10.37394/23206.2023.22.1.

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Over the years, scholars have developed predictor-corrector method to provide estimates for ordinary differential equations (ODEs). Predictor-corrector methods have been reduced to predicting-correcting method with no concern for finding the convergence-criteria for each loop with no suitable vary step size in order to maximize error. This study aim to consider computing fuzzy differential equations employing the extended block predictor-block corrector method (EBP-BCM). The method of interpolation and collocation combined with multinomial power series as the basis function approximation will

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18

Oghonyon, J. G., S. A. Okunuga, K. S. Eke, and O. A. Odetunmibi. "Block Milne’s Implementation For Solving Fourth Order Ordinary Differential Equations." Engineering, Technology & Applied Science Research 8, no. 3 (2018): 2943–48. http://dx.doi.org/10.48084/etasr.1914.

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Block predictor-corrector method for solving non-stiff ordinary differential equations (ODEs) started with Milne’s device. Milne’s device is an extension of the block predictor-corrector method providing further benefits and better results. This study considers Milne’s devise for solving fourth order ODEs. A combination of Newton’s backward difference interpolation polynomial and numerical integration method are applied and integrated at some selected grid points to formulate the block predictor-corrector method. Moreover, Milne’s devise advances the computational efficiency by applying the pr

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19

Liu, Chao, and Hui Wang. "A real-time predictor-modification-evaluation–corrector-modification-evaluation parametric interpolator for numerical control transition curves." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 234, no. 1-2 (2019): 95–107. http://dx.doi.org/10.1177/0954405419856951.

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A real-time parametric interpolator based on a predictor-modification-evaluation–corrector-modification-evaluation algorithm is proposed in this article, which is utilized to efficiently calculate the reference points of transition curves. Meanwhile, the stable calculation is guaranteed by analyzing the convergence condition of the predictor-modification-evaluation–corrector-modification-evaluation algorithm. Under the convergence condition, the proposed parametric interpolator and traditional line interpolators are simultaneously implemented to interpolate a two-dimensional butterfly path, wh

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20

Nwankwo, Chinonso, and Weizhong Dai. "Efficiency of Some Predictor–Corrector Methods with Fourth-Order Compact Scheme for a System of Free Boundary Options." Axioms 12, no. 8 (2023): 762. http://dx.doi.org/10.3390/axioms12080762.

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The trade-off between numerical accuracy and computational cost is always an important factor to consider when pricing options numerically, due to the inherent irregularity and existence of non-linearity in many models. In this work, we first present fast and accurate (1,2) and (2,2) predictor–corrector methods with a fourth-order compact finite difference scheme for pricing coupled system of the non-linear free boundary option pricing problem consisting of the option value and delta sensitivity. To predict the optimal exercise boundary, we set up a high-order boundary scheme, which is strateg

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21

Adetola Olaide, Adesanya, M. R. Odekunle, and A. O. Adeyeye. "Continuous Block-Predictor Hybrid-Corrector Method." International Journal of Mathematics and Soft Computing 2, no. 2 (2012): 35. http://dx.doi.org/10.26708/ijmsc.2012.2.2.05.

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22

Salahi, M., J. Peng, and T. Terlaky. "On Mehrotra-Type Predictor-Corrector Algorithms." SIAM Journal on Optimization 18, no. 4 (2008): 1377–97. http://dx.doi.org/10.1137/050628787.

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23

Martyna, Glenn J., and Mark E. Tuckerman. "Symplectic reversible integrators: Predictor–corrector methods." Journal of Chemical Physics 102, no. 20 (1995): 8071–77. http://dx.doi.org/10.1063/1.469006.

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24

Usman, Anila, and George Hall. "Equilibrium states for predictor-corrector methods." Journal of Computational and Applied Mathematics 89, no. 2 (1998): 275–308. http://dx.doi.org/10.1016/s0377-0427(97)00239-2.

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25

Salahi, Maziar, and Tamás Terlaky. "Mehrotra-type predictor-corrector algorithm revisited." Optimization Methods and Software 23, no. 2 (2008): 259–73. http://dx.doi.org/10.1080/10556780701661393.

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26

Wang, Tao, Hongbo Zhang, Liang Zeng, and Guojian Tang. "A robust predictor–corrector entry guidance." Aerospace Science and Technology 66 (July 2017): 103–11. http://dx.doi.org/10.1016/j.ast.2017.03.010.

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27

Barton, I. E. "Exponential-Lagrangian Tracking Schemes Applied to Stokes Law." Journal of Fluids Engineering 118, no. 1 (1996): 85–89. http://dx.doi.org/10.1115/1.2817520.

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The exponential-Lagrangian tracking scheme applied to Stokes Law is developed by introducing a predictor-corrector formulation. The new predictor-corrector schemes are more accurate than the original scheme and are estimated to give a better performance taking into account the increased computational effort. The schemes are tested on two simple problems and the results are compared with the analytical solutions.

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28

Balbo, Antonio Roberto, Márcio Augusto da Silva Souza, Edméa Cássia Baptista, and Leonardo Nepomuceno. "Predictor-Corrector Primal-Dual Interior Point Method for Solving Economic Dispatch Problems: A Postoptimization Analysis." Mathematical Problems in Engineering 2012 (2012): 1–26. http://dx.doi.org/10.1155/2012/376546.

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This paper proposes a predictor-corrector primal-dual interior point method which introduces line search procedures (IPLS) in both the predictor and corrector steps. The Fibonacci search technique is used in the predictor step, while an Armijo line search is used in the corrector step. The method is developed for application to the economic dispatch (ED) problem studied in the field of power systems analysis. The theory of the method is examined for quadratic programming problems and involves the analysis of iterative schemes, computational implementation, and issues concerning the adaptation

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29

Kheirfam, Behrouz. "A predictor-corrector path-following algorithm for symmetric optimization based on Darvay's technique." Yugoslav Journal of Operations Research 24, no. 1 (2014): 35–51. http://dx.doi.org/10.2298/yjor120904016k.

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In this paper, we present a predictor-corrector path-following interior-point algorithm for symmetric cone optimization based on Darvay's technique. Each iteration of the algorithm contains a predictor step and a corrector step based on a modification of the Nesterov and Todd directions. Moreover, we show that the algorithm is well defined and that the obtained iteration bound is o(?rlogr?/?), where r is the rank of Euclidean Jordan algebra.

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30

Ibrahimov, Vagif, Gabriel Xiao-Guang Yue, and Davron Aslonqulovich Juraev. "On Some Advantages of the Predictor-Corrector Methods." IETI Transactions on Data Analysis and Forecasting (iTDAF) 1, no. 4 (2023): 79–89. http://dx.doi.org/10.3991/itdaf.v1i4.46543.

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Usually, all numerical methods are divided into two sets known as explicit and implicit methods. Explicit methods (EM) are used to find a solution to a problem directly, without requiring initial preparation. But when using the implicit method (IM), other methods can sometimes be employed. Implicit methods are known to be more accurate than explicit ones. Therefore, the question arises about finding the golden mean. To accomplish this, we utilize certain properties of the predictor and corrector methods. We take into account that in forecasting methods, we use EM. However, I will show here tha

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31

Sultana, Mariam, Uroosa Arshad, Muhammad Khalid, Ali Akgül, Wedad Albalawi, and Heba Y. Zahran. "A New Iterative Predictor-Corrector Algorithm for Solving a System of Nuclear Magnetic Resonance Flow Equations of Fractional Order." Fractal and Fractional 6, no. 2 (2022): 91. http://dx.doi.org/10.3390/fractalfract6020091.

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Nuclear magnetic resonance flow equations, also known as the Bloch system, are said to be at the heart of both magnetic resonance imaging (MRI) and nuclear magnetic resonance (NMR) spectroscopy. The main aim of this research was to solve fractional nuclear magnetic resonance flow equations (FNMRFEs) through a numerical approach that is very easy to handle. We present a New Iterative Predictor-Corrector Algorithm (NIPCA) based on the New Iterative Algorithm and Predictor-Corrector Algorithm to solve nonlinear nuclear magnetic resonance flow equations of fractional order involving Caputo derivat

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32

Mostak, Ahmed, Mehadi Hasan Md., and Abdullah Bin Masud Md. "An Error Attenuating Predictor-Corrector Approach for Stiff Systems of Ordinary Differential Equations." Journal of Applied Mathematics and Statistical Analysis 3, no. 2 (2022): 1–10. https://doi.org/10.5281/zenodo.6844855.

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<em>This work involves the use of an error attenuating predictor-corrector approach (EAPCA) for both fixed and variable step-size to solve systems of ordinary differential equations (ODEs) in both linear and nonlinear cases, focusing interest on stiff problems. Apart from the traditional predictor-corrector (TPC) method where each corrector corrects the prediction once at each step, our proposed scheme will refine the results more precisely by infusing a tolerance meeting point on each corrector method which will make corrections until it satisfies the given tolerance. Four well-known stiff sy

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33

Cidar Iyikal, Ovgu. "Numerical Solution of Sylvester Equation Based on Iterative Predictor-Corrector Method." Journal of Mathematics 2022 (August 22, 2022): 1–7. http://dx.doi.org/10.1155/2022/6571126.

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The inspiration of the study concerns an iterative predictor-corrector method with order of convergence p = 45 for computing the inverse of the coefficient matrix Λ = I n ⊗ A + B T ⊗ I m , which is obtained by the Sylvester equation A X + X B = C . The numerical solutions of three examples by predictor-corrector algorithm are given. The final numerical results also support the applicability, fast convergency, and high accuracy of the method for finding matrix inverses.

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34

Liu, Yilin, Xuqiang Shao, and Zhaohui Wu. "Rotation Invariant Predictor-Corrector for Smoothed Particle Hydrodynamics Data Visualization." Symmetry 13, no. 3 (2021): 382. http://dx.doi.org/10.3390/sym13030382.

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In order to extract the vortex features more accurately, a new method of vortex feature extraction on the Smoothed Particle Hydrodynamics data is proposed in the current study by combining rotation invariance and predictor-corrector method. There is a limitation in the original rotation invariance, which can only extract the vortex features that perform equal-speed rotations. The limitation is slightly weakened to a situation that the rotation invariance can be used, given that a specific axis is existed in the fluid to replace the axis needed for it. Therefore, as long as the axis exists, the

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35

Ting, Yung, Tho Van Nguyen, and Jia-Ci Chen. "Design and performance evaluation of an exponentially weighted moving average–based adaptive control for piezo-driven motion platform." Advances in Mechanical Engineering 10, no. 6 (2018): 168781401876719. http://dx.doi.org/10.1177/1687814018767194.

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In this article, building a controlled system with velocity feedback in the inner loop for a platform driven by piezoelectric motors is investigated. Such a motion control system is subject to disturbance such as friction, preload, and temperature rise in operation. Especially, temperature rise is an essential problem of using piezoelectric motor, but very few research works address this topic in depth. Exponentially weighted moving average method has been widely used in process control to deal with systematic change and drift disturbance. It is attempted to map the exponentially weighted movi

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36

Yao, Dongdong, and Qunli Xia. "Predictor–Corrector Guidance for a Hypersonic Morphing Vehicle." Aerospace 10, no. 9 (2023): 795. http://dx.doi.org/10.3390/aerospace10090795.

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In an effort to address the problem of hypersonic morphing vehicles reaching the target while avoiding no-fly zones, an improved predictor–corrector guidance method is proposed. Firstly, the aircraft motion model and the constraint model are established. Then, the basic algorithm is given. The Q-learning method is used to design the attack angle and sweep angle scheme to ensure that the aircraft can fly over low-altitude zones. The B-spline curve is used to determine the locations of flight path points, and the bank angle scheme is designed using the predictor–corrector method, so that the air

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37

Kheirfam, Behrouz. "A corrector–predictor path-following algorithm for semidefinite optimization." Asian-European Journal of Mathematics 07, no. 02 (2014): 1450028. http://dx.doi.org/10.1142/s1793557114500284.

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A corrector–predictor algorithm is proposed for solving semidefinite optimization problems. In each two steps, the algorithm uses the Nesterov–Todd directions. The algorithm produces a sequence of iterates in a neighborhood of the central path based on a new proximity measure. The predictor step uses line search schemes requiring the reduction of the duality gap, while the corrector step is used to restore the iterates to the neighborhood of the central path. Finally, the algorithm has [Formula: see text] iteration complexity.

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38

Ma, Xiaojue, Hongwei Liu, and Chang Zhou. "A Predictor–Corrector Algorithm for Monotone Linear Complementarity Problems in a Wide Neighborhood." International Journal of Bifurcation and Chaos 25, no. 14 (2015): 1540035. http://dx.doi.org/10.1142/s0218127415400350.

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We propose a new primal-dual interior-point predictor–corrector algorithm in Ai and Zhang’s wide neighborhood for solving monotone linear complementarity problems (LCP). Based on the understanding of this neighborhood, we use two new directions in the predictor step and in the corrector step, respectively. Especially, the use of new corrector direction also reduces the duality gap in the corrector step, which has good effects on the algorithm’s convergence. We prove that the new algorithm has a polynomial complexity of [Formula: see text], which is the best complexity result so far. In the pap

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39

Oghonyon, Jimevwo Godwin, Solomon Adebola Okunuga, and Samuel Azubuike Iyase. "Milne’s Implementation on Block Predictor-corrector Methods." Journal of Applied Sciences 16, no. 5 (2016): 236–41. http://dx.doi.org/10.3923/jas.2016.236.241.

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40

Krivovichev, G. V., and E. V. Voskoboinikova. "Predictor-corrector finite-difference lattice Boltzmann schemes." Applied Mathematical Sciences 9 (2015): 4191–99. http://dx.doi.org/10.12988/ams.2015.5138.

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41

Bonelli, Alessio, and Oreste S. Bursi. "Predictor‐corrector procedures for pseudo‐dynamic tests." Engineering Computations 22, no. 7 (2005): 783–834. http://dx.doi.org/10.1108/02644400510619530.

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42

Birta and Abou-Rabia. "Parallel Block Predictor–Corrector Methods for Ode's." IEEE Transactions on Computers C-36, no. 3 (1987): 299–311. http://dx.doi.org/10.1109/tc.1987.1676902.

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43

Hauenstein, Jonathan D., and Alan C. Liddell. "Certified predictor–corrector tracking for Newton homotopies." Journal of Symbolic Computation 74 (May 2016): 239–54. http://dx.doi.org/10.1016/j.jsc.2015.07.001.

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44

Sun, Zhiyuan, Jun Liu, and Pei Wang. "The predictor-corrector algorithm for hourglass control." Computers & Fluids 209 (September 2020): 104644. http://dx.doi.org/10.1016/j.compfluid.2020.104644.

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45

Platen, Eckhard. "On weak implicit and predictor-corrector methods." Mathematics and Computers in Simulation 38, no. 1-3 (1995): 69–76. http://dx.doi.org/10.1016/0378-4754(93)e0068-g.

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46

Ghrist, Michelle L., Bengt Fornberg, and Jonah A. Reeger. "Stability ordinates of Adams predictor-corrector methods." BIT Numerical Mathematics 55, no. 3 (2014): 733–50. http://dx.doi.org/10.1007/s10543-014-0528-7.

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47

Zhang, Ju-liang, Xiang-sun Zhang, and Yong-mei Su. "Predictor-Corrector Smoothing Methods for Monotone LCP." Acta Mathematicae Applicatae Sinica, English Series 20, no. 4 (2004): 557–72. http://dx.doi.org/10.1007/s10255-004-0193-8.

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48

Inayat Noor, Khalida, and Muhammad Aslam Noor. "Predictor–corrector Halley method for nonlinear equations." Applied Mathematics and Computation 188, no. 2 (2007): 1587–91. http://dx.doi.org/10.1016/j.amc.2006.11.023.

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49

Luo, Zhiquan, Shiquan Wu, and Yinyu Ye. "Predictor-corrector method for nonlinear complementarity problem." Acta Mathematicae Applicatae Sinica 13, no. 3 (1997): 321–28. http://dx.doi.org/10.1007/bf02025887.

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50

Syamsudhuha, Syamsudhuha, Widari Cania, M. Imran, Ayunda Putri, Rike Marjulisa, and Supriadi Putra. "A SIXTH-ORDER PREDICTOR-CORRECTOR METHOD FOR INITIAL VALUE PROBLEMS." Journal of Mathematical Sciences and Optimization 2, no. 2 (2025): 135–43. https://doi.org/10.31258/jomso.v2i2.39.

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This article discusses the sixth-order predictor-corrector method by changing the integral limit of $[t_n,t_{n+1}]$ to $[t_{n-3},t_{n+1}]$. This method combines the explicit Adam-Bashforth approach as a predictor and the implicit Adam-Moulton approach as corrector. The results obtained show that the numerical solution is close to the exact solution and the selection of a small \textit{stepsize} $h$ makes this method an alternative method in solving various initial value problems.

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