A numerical algorithm for regularization of the solution of the source problem for the diffusion-logistic model based on information about the process at fixed moments of time of integral type has been developed. The peculiarity of the problem under study is the discrete formulation in space and impossibility to apply classical algorithms for its numerical solution. The regularization of the problem is based on the application of A.N. Tikhonov's approach and a priori information about the source of the process. The problem was formulated in a variational formulation and solved by the global tensor optimization method. It is shown that in the case of noisy data regularization improves the accuracy of the reconstructed source.

翻译：基于积分型过程在固定时刻的信息，开发了一种用于扩散-逻辑模型源问题解正则化的数值算法。所研究问题的特点在于空间上的离散表述以及无法应用经典算法进行数值求解。该问题的正则化基于A.N. Tikhonov方法的应用以及关于过程源的先验信息。问题被表述为变分形式，并通过全局张量优化方法求解。研究表明，在数据含噪的情况下，正则化可提高重建源的精度。