Solutions of fractional order differential equations with laplace transforms

In recent years, fractional ordered derivatives have become increasingly common in various scientific disciplines, especially in the field of applied mathematics. Despite the existence of a large number of definitions for fractional order derivatives in the literature, there is a notable shortage of studies evaluating the effectiveness of different definitions of derivatives within mathematical models. In this thesis, two fractional grey models were created with the same structure as Caputo and Conformable derivative operators and their applications were included in the same data sets. Applications reveal that the Conformable derivative operator facilitates simpler calculations due to the inherent simplicity of the derivative definition. Conversely, the Caputo derivative operator, known for its effectiveness in time series-related models due to its memory property, requires more complex calculations. The solution of the whitening differential equation in the Caputo fractional gray model was provided by Laplace transformations. The comparison was carried out by applying Caputo and Conformable fractional gray models to predict three real-time series, and the respective prediction performances were systematically evaluated. This study represents the first example in the literature where Caputo and Conformable derivative operators are compared in the context of a gray model.