In practice, one often encounters large-scale computational problems and optimization problems, so that the complexity, computation and computational accuracy of algorithms for solving these problems become a prominent issue, especially for the identification algorithms of large-scale nonlinear multi-variable systems. Therefore, the interesting research projects are proposed as follows: 1) the information filtering technology and the multi-innovation identification theory are used to study the identification methods for large-scale nonlinear systems, which can improve the identification accuracy; 2) the hierarchical identification principle is used to study the hierarchical identification methods for multi-variable systems with high dimensionalities and more variables so as to reduce computational complexity; 3) the martingale convergence theory is used to establish the convergence theory of the identification methods for nonlinear multi-variable systems; 4) the parallel computing and the hierarchical computation are used to enhance the computational efficiency so as to solve the modeling problems of a class of large-scale nonlinear multi-variable systems.