Purpose of the study: development of a new universal fuzzy-multiple methodology that allows assessing the effectiveness of reforestation based on a variable set of indicators, the significance of which is taken into account on the basis of expert assessments, in contrast to existing assessment methods. The systems of fuzzy-logical conclusions, the so-called standard multilevel [0,1] classifiers, were used as a mathematical tool for constructing the assessment methodology. As a result of the implementation of the methodology, an assessment of reforestation in the Rostov region was carried out on the basis of a set of 23 indicators characterizing the dynamics of reforestation, thinning activities, and patrolling of the forest fund in the region. In comparison with the already existing estimation methods, the proposed estimation method has a number of such advantages, such as: simple calculation scheme; when constructing estimates, taking into account a large number of heterogeneous significant indicators that can vary depending on the available statistical material and the characteristics of the specific practical problem being solved; the possibility of varying the weight of the contribution of the studied indicators to the corresponding comprehensive assessment; the possibility of analyzing on its basis the situation in the region under consideration.

研究目的：开发一种新的通用模糊多重方法，允许根据一组可变指标评估重新造林的有效性，与现有评估方法相比，其重要性在专家评估的基础上被考虑在内. 模糊逻辑结论系统，即所谓的标准多级[0,1]分类器，被用作构建评估方法的数学工具。作为实施该方法的结果，罗斯托夫地区的重新造林评估是根据一组 23 项指标进行的，这些指标描述了该地区重新造林、疏伐活动和森林基金巡逻的动态。与现有的估算方法相比，所提出的估计方法具有许多这样的优点，例如：简单的计算方案；在构建估计值时，考虑到大量异质的重要指标，这些指标可能会因可用的统计材料和正在解决的具体实际问题的特征而异；改变研究指标对相应综合评估的贡献权重的可能性；在此基础上分析所考虑地区局势的可能性。改变研究指标对相应综合评估的贡献权重的可能性；在此基础上分析所考虑地区局势的可能性。改变研究指标对相应综合评估的贡献权重的可能性；在此基础上分析所考虑地区局势的可能性。