Influence of Pareto optimality on the maximum entropy methods

Galerkin meshfree schemes are emerging as a viable substitute to finite element method to solve partial differential equations for the large deformations as well as crack propagation problems. However, the introduction of Shanon-Jayne’s entropy principle in to the scattered data approximation has deviated from the trend of defining the approximation functions, resulting in maximum entropy approximants. Further in addition to this, an objective functional which controls the degree of locality resulted in Local maximum entropy approximants. These are based on information-theoretical Pareto optimality between entropy and degree of locality that are defining the basis functions to the scattered nodes. The degree of locality in turn relies on the choice of locality parameter and prior (weight) function. The proper choices of both plays vital role in attain the desired accuracy. Present work is focused on the choice of locality parameter which defines the degree of locality and priors: Gaussian, Cubic spline an...