In this method to tell whether one DMU is DEA efficient or not is based on the frontier of real sample points, so it is called Data Envelopment Analysis.
由于该方法中判断某个决策单元是否DEA有效，是以各实际样本点的外包络面为基础的，因此称为数据包络分析。
Based on this, all the DMUs are classified into three types, which are interval DEA efficient, interval DEA partly efficient and interval DEA unefficient.
然后按区间效率值将所有决策单元分为三类，即区间DEA有效、区间DEA部分有效和区间DEA无效。
The sample DEA has an active function on giving an order of units, risk evaluation, analyzing of DEA efficient units and forecasting the combination efficiency of some units.
基于样本的DEA方法在择优排序，风险评估，分析有效单元性质，预测组合有效性等方面具有积极的作用。
By utilizing the project analysis on DEA efficient frontier, the adjustment quantity of inefficient DMU input indexes are ensured, and it can provide reliable basis for optimizing materiel cost scale.
最后利用决策单元在相对有效前沿面上的投影分析，明确了非有效单元投入指标的调整量，为优化装备费用规模提供决策支持。
Then a C2R Data Envelopment Analysis (DEA) decision model with multi-input and output was built to assess whether technique and scale were simultaneously efficient.
在此基础上，建立了基于技术与规模同时有效的多投入多产出的C2R数据包络分析决策模型。
The preference DEA model is put forward based on the traditional DEA model to solve the comprehensive evaluation, and to solve the same efficient DMU with the average cross-efficiency.
在对传统DEA模型修正的基础上，提出了应用偏好序DEA模型来对信息系统综合评价，并提出用平均横切效率来解决同为有效决策单元的对比问题。
The preference DEA model is put forward based on the traditional DEA model to solve the comprehensive evaluation, and to solve the same efficient DMU with the average cross-efficiency.
在对传统DEA模型修正的基础上，提出了应用偏好序DEA模型来对信息系统综合评价，并提出用平均横切效率来解决同为有效决策单元的对比问题。
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