A Modified Multiple Shooting Algorithm for Parameter Estimation in ODEs Using Adjoint Sensitivity Analysis

To increase the predictive power of a model, one needs to estimate its unknown parameters. Almost all parameter estimation techniques in ordinary differential equation models suffer from either small convergence region or enormous computational cost. The method multiple shooting, on other hand, takes place between these two extremes. cost algorithm is mostly due calculation directional derivatives objective and constraint functions. Here we modify shooting use adjoint calculating derivatives. In literature, this known be more stable computationally efficient way computing gradients scalar A predator-prey system used show performance supply necessary information for successful implementation.