最小区域法是符合最小条件的一种直线度误差评定方法，但较难实现。
The minimum zone method meets the minimum condition for evaluating the straightness, however it is difficult to accomplish computerization.
用最小区域法求直线度误差，是在最小二乘法的基础上探讨的一种符合最小条件的新方法。
Computing straightness error on the basis of least square method by way of smallest field method is new method in exploring the minimum condition.
提出一种基于MATLAB的圆度评定方法，利用MATLAB优化工具箱，为采用最小区域圆法、最小二乘圆法、最小外接圆法和最大内接圆法实现圆度的评定提供了新的选择。
By using MATLAB optimization toolbox, the method has supplied a new selection to assess roundness with taking MZC, LSC, MCC and MIC as its reference circle.
提出了一种新的居住小区满意度评测方法——将改进的层次分析法和模糊综合评价法相结合进行评测。
This paper puts forward a new method combining the improved analysis hierarchy process (AHP) with the fuzzy synthetic evaluation to evaluate satisfactory degree of an uptown.
采用径流小区法研究等高梯地、荒草地、侵蚀地三种类型水土肥流失及其变化特点。
In the plot experiment on runoff, the loss of water, soil and fertilizer and the characteristics of contour terrace, grass wasteland and eroded soil were studied.
区域OD合并模块是按照一定的算法将单个调查点od矩阵合并为区域内小区间的总od，本系统主要采用两种算法：串联法和平行路法。
Regional od integration module integrates every single-point od into total regional od by special algorithm. In the system two algorithms are used: series-parallel and parallel road.
提出了一种满足最小区域法的曲面形状误差评定方法。
A method for calculating the surface form error with the requirements of the minimal zone is proposed.
提出一种用最小区域法进行误差评判时的数据处理算法——最佳脊线法。
This paper introduces the application of computers in the measuring system from a new perspective, and puts forward an algorithm to judging the errors with the minimum area principle.
介绍了基于三角模糊数的模糊层次分析法，及其在某小区电网规划方案综合评判中应用的过程，为城市电网规划决策综合评判提供了一种新方法。
This paper introduces a FAHP based MADM method in urban power system planning and the procedure of applying this method. The method will be a new way for urban power system planning MADM.
提出了一种满足最小区域法的空间直线度误差评价的新方法一粒子群算法。
A method to evaluate spatial straightness errors adopting particle swarm optimization (PSO) is proposed.
提出了一种满足最小区域法的空间直线度误差评价的新方法一粒子群算法。
A method to evaluate spatial straightness errors adopting particle swarm optimization (PSO) is proposed.
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