Meshless local discrete Galerkin method for solving a system of ordinary differential equations arisen from cancer cell population growth

The use of mathematical models to simulate dynamic biological processes has a long history. The main purpose of this paper is to investigate a computational method to solve the growth model of cancer cells. This method is based on the use of moving least squares (MLS) approximation functions constructed on scattered points in the discrete Galerkin method. The moving least squares method is an effective technique for approximating an unknown function that involves a locally weighted least squares polynomial fitting. The algorithm of the proposed scheme is computationally attractive and easy to implement on computers. The validity and efficiency of the offered technique are demonstrated through one numerical example.