choosing a simulation solver -凯发k8网页登录

ode solvers — these include nonstiff deterministic solvers and stiff deterministic solvers. the solver functions implement numerical integration methods for solving initial value problems for ordinary differential equations (odes). beginning at the initial time with initial conditions, they step through the time interval, computing a solution at each time step. if the solution for a time step satisfies the solver's error tolerance criteria, it is a successful step. otherwise, it is a failed attempt; the solver shrinks the step size and tries again. for more information, see ode solvers.

sundials solvers — at a fundamental level the core algorithms for the sundials solvers are similar to those for some of the solvers in the matlab^® ode suite and work as described above in ode solvers. simbiology always uses the sundials solver to perform sensitivity analysis on a model, regardless of what you have selected as the . for more information, see sundials solvers.

stochastic solvers — use with models containing a small number of molecules. stochastic solvers include stochastic simulation algorithm, explicit tau-leaping algorithm, and implicit tau-leaping algorithm. for more information, see stochastic solvers.