Quadrature Integration Techniques for Random Hyperbolic PDE Problems

In this paper, we consider random hyperbolic partial differential equation (PDE) problems following the mean square approach and Laplace transform technique. Randomness requires not only computation of approximating stochastic processes, but also its statistical moments. Hence, appropriate numerical methods should allow for efficient expectation variance. Here, analyse different around inverse evaluation by using several integration techniques, including midpoint quadrature rule, Gauss–Laguerre extensions, Talbot algorithm. Simulations, convergence, computational process time with experiments are shown.