For Elzaki & Ezaki, (2011) solving differential equation to some extent involves the use of different code which are mostly unavailable for a time dependent event and another for non-time dependent. The effect of such computational always result the problem of approximating the answer since they are very complex and they require an expertise in computational mathematics to write the code for execution (Yuanlu, 2010). According to Yao & Chen (2013), solving FDEs is not an easy task but not saying it is impossible, as majority of the time that they are solved numerically by using some computational tools. Solving FDEs has been recognized by researchers as a daunty task due to the numerous technique available (sheun et al., 2019). thus, in this project, the researchers will only use Caputo fractional displacement, thanks to its application to real models The derivatives of this whole sequence represent the characteristics of the observable physical state, and therefore their value can be measured accurately.
An alternative definition of fractional derivatives obtained after the detection and integration of interchangeable differences is the so -called Caputo derivative, which for sufficient functional variation has only the advantage of requiring initial conditions assigned to the overall derivative conditions of the order. Yuanlu, (2010) described it as a derivative without explicit physical interpretation, and therefore initial probabilistic values are required to be immediately available.
When used in mathematical models, fractional Riemann-Liouville derivatives require initial conditions to be expressed in fractional integrals. Variant derivatives, which have traditionally been defined and studied by mathematicians, are derivatives of Riemann Liouville fractions but are not always the most appropriate definition for actual applications. Regardless of the large number of definitions of unequal fractional derivatives that are widely used, and this study focuses on a specific form (called the Caputo derivative version) (Yao & Chen, 2013). As a result, various methods have been developed to provide numerical solutions for FDE, such as viscoelasticity and damping, wave propagation and propagation, and turbulence (Zhu, 2012). Yi (2013) further noted that the concept of derivatives derived from variable sequences has also been introduced and several related practical application research papers have emerged.ĭue to the breakdown of fractional orders in differential operators, FDE analysis solutions are usually difficult to obtain. in like manner, there are also several mathematical tools or integrated development environments (IDEs) (such as MATLAB, Python, Mathematica, and Maple) that provide efficiency, reliability, and simplicity – use the code to solve the differential equation numerically. Moreover, orthogonal functions also play an important role in finding numerical solutions for FDE, such as Pulse Pulse function (Yi, 2013), Bernstein polynomial (Saadatmandi, 2014), replaced by Legendre polynomial (Khalil, 2014), Chebyshev wavelets (Zhu, 2012), Legendre Wave (Heydari, 2014), etc. The most commonly used is the Adomian decomposition method (ADM) (El-Kalla, 2011 Ahmed, 1998), General differential modification technique (GDTM) (Shaher, 2007 Zaid, 2008 Shaher, 2008), wave method (Li Zhu, 2012 Mingxu, 2012), difference method to (Deng, 2013), Laplace transformation method (Gupta, 2014), variation iteration method (Odibat, 2006), fractional variation transformation method (Arikoglu, 2009), operational strategy (Luchko, 1999 Li, 2013 Bengochea, 2014) and other methods (Zaid, 2009 Kai, 2004 Javidi, 2009). Several numerical methods using different types of derivative operators to solve different types of fractional measures have been proposed. according to Abell & Braselton (2016) one of the major advantages of fractional calculus is that fractional derivatives provide a superior approach to describing the memory and hereditary properties of a variety of materials and processes.
Though therer are various types of differential equation which the numerical method can be used to solve, this project, focuses on “fractional fractional equations.” this follows the fact that In recent years, fractional calculus has attracted the attention of more well established scholars and many successful researchers in from various fields of science and engineering (Abell & Braselton 2016). according to numerical analysis is a valuable tool to generate and evaluate methods for calculating numerical information from a giving data set. Numerical analysis is a branch of mathematics that studies quantitative methods for solving complex equations using arithmetic operations, often so complex that it requires a computer to estimate the process of analysis (i.e. Research Project Chapter 1-3 Sample – NUMERICAL METHODS FOR SOLVING DIFFERENTIAL EQUATIONS