【摘要】 产品研发过程中功能优化是一个复杂系统，往往存在大量随机且不确定性因素。不确定可靠性是解决这类问题的一个重要数学工具。引入人工智能机器学习中Rényi熵，构建基于Rényi熵的不确定可靠性产品功能优化模型及自动化计算方法。通过产品功能需求分析、认知集合转换、Rényi熵可信度分配与合成等过程，自动化迭代计算出优选功能组合。以应急救援产品为例，计算结果表明，产品功能优化算法模型能够有效抑制不确定性因素扰动，获取最优解组合，提高产品设计效率及准确性。更多还原

【Abstract】 Function optimization is a complex system in the process of product development, which is affected by a large number of random and uncertain factors. Uncertain reliability is an important mathematical tool aimed to solve this kind of problems. In this paper, Rényi entropy is introduced to construct the uncertain reliability function optimization model and the automatic calculation method. Through analysis of the product functional requirements, conversion of the cognitive set, Rényi entropy reliability distribution and synthesis, the optimal function combination is automatically calculated. Taking the emergency rescuing product as an example, the calculation results show that the product function optimization algorithm model can suppress the disturbance from uncertain factors effectively, obtain the optimal solution combination, and improve the efficiency and accuracy of product design.更多还原