Under the influence of the COVID-19 epidemic situation, many countries have taken many measures to control the flow of people. The inability of people to gather makes art color measurement a problem. Color matching and coordination and color space conversion have always been the research focus of art color measurement. This paper studies a method of fuzzy intelligent reasoning in art color measurement. Based on case-based reasoning and rule-based reasoning, this method is an important self-learning and self-maintenance method in the field of artificial intelligence and expert system. On the basis of expounding the basic characteristics of color and color space, this paper designs the process principle of case-based reasoning and the process of rule-based reasoning. In this paper, case and rule knowledge representation method, case retrieval technology and rule conflict resolution strategy are established. Based on the above strategy, the color case base is established. In addition, the rule table is established by combining color-brewer with rule reasoning and referring to color-brewer. The rule table has a certain reference value for the application of intelligent reasoning method in the field of art color measurement under the influence of COVID-19 epidemic.

中文翻译：

---

模糊智能推理方法在艺术品色彩测量中的应用

在COVID-19疫情的影响下，许多国家采取了许多措施来控制人流。人们无法聚集使得艺术品色彩测量成为一个问题。色彩匹配和协调以及色彩空间转换一直是艺术色彩测量的研究重点。本文研究了一种艺术色彩测量中的模糊智能推理方法。该方法基于案例推理和规则推理，是人工智能和专家系统领域的一种重要的自学习和自维护方法。在阐述色彩和色彩空间的基本特征的基础上，设计了基于案例的推理过程原理和基于规则的推理过程。本文采用案例和规则知识表示方法，建立了案例检索技术和规则冲突解决策略。基于以上策略，建立了颜色案例库。另外，规则表是通过将颜色激励器与规则推理相结合并引用颜色激励器而建立的。该规则表对于在COVID-19流行病影响下的智能推理方法在艺术色彩测量领域的应用具有一定的参考价值。