Data Envelopment Analysis (DEA) is a mathematical programming approach to assess the relative efficiencies of decision making units with multiple inputs and outputs.
DEA是评价一组具有多输入和多输出的决策单元相对效率的数学规划方法。
参考来源 - 基于变量属性分类的DEA模型研究It involves a lot of intercross subjects and technologies such as machine learning, mathematical programming, statistics, pattern recognition and so on.
它是一门交叉学科,涉及机器学习、数学规划、数理统计、模式识别等相关技术。
参考来源 - 支持向量机模型和算法研究·2,447,543篇论文数据，部分数据来源于NoteExpress
以上来源于: WordNet
Solve the mathematical programming problem.
数学规划问题求解。
How to solve it is much more complex than that of ordinary mathematical programming because of its random coefficients.
由于在系数中引入了随机变量，使得随机规划问题的求解比普通的数学规划要复杂得多。
Therefore, the research on convexity and generalized convexity is one of the most important aspects in mathematical programming.
因此，对凸函数和广义凸函数的研究是数学规划中最重要的内容之一。
应用推荐