Nonparametric methods for solving the data reconciliation problem

Garanin V. A., Semenov K. K. Nonparametric methods for solving the data reconciliation problem. This work explores the current state of industrial data reconciliation, examining key approaches to addressing this problem in both classical and nonclassical contexts. The article provides a comprehensive overview of the main directions in this field and introduces novel contributions by the authors. These include approaches to nonparametric data reconciliation and a new method that revisits the analytical solution with the modern requirements to the restrictions on the reconciliation final results and at the current level of problem complexity. It offers closed-form expressions that enable the independent and targeted optimization of the industrial data reconciliation process for specific conditions —- a development not previously achieved. Finally, this paper aims to address the gap in the field of data reconciliation in Russian-language scientific literature.