Application of a robust statistics based fuzzy comprehensive evaluation method in quality assessment between coal property laboratories

HAO Zhenda; ZHANG Hongliang; KONG Xiangming; LI Wei; HUANG Guohe

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Application of a robust statistics based fuzzy comprehensive evaluation method in quality assessment between coal property laboratories

Thermal Power Generation Vol. 43, Issue 1, Pages: 85-89(2014)

更新时间：2025-09-28

- Application of a robust statistics based fuzzy comprehensive evaluation method in quality assessment between coal property laboratories
- 作者机构：
  
  1. 华北电力大学区域能源系统优化教育部重点实验室
  2. 广东电网公司电力科学研究院
- 作者简介：
- 基金信息：
- DOI：
  CLC： TQ533
- Published：2014
- 稿件说明：
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HAO Zhenda, ZHANG Hongliang, KONG Xiangming, et al. Application of a robust statistics based fuzzy comprehensive evaluation method in quality assessment between coal property laboratories[J]. Thermal Power Generation, 2014, 43(1): 85-89.
DOI：

HAO Zhenda, ZHANG Hongliang, KONG Xiangming, et al. Application of a robust statistics based fuzzy comprehensive evaluation method in quality assessment between coal property laboratories[J]. Thermal Power Generation, 2014, 43(1): 85-89. DOI：

摘要

将稳健统计分析中的能力统计量Z比分数与模糊综合评价相结合

建立了Z比分数-模糊综合评价模型。该模型可建立一组用于多因素集中所有元素的模糊隶属度函数

以进行整体判断和描述

降低了运算复杂度。以某烟煤为检测对象

对34个煤质实验室检的测结果进行分析

结果表明

Z比分数-模糊综合评价模型克服了稳健统计分析和模糊综合评价的不足

适用于多因素集、多指标集的煤质实验室检测能力比对。

Abstract

Combining the Z-score from the robust statistics analysis method with fuzzy comprehensive evaluation(FCE)method

a Z score-fuzzy comprehensive evaluation model was established. This model is applied to a case study in ability evaluation of coal labs.The test result was transferred into Z scores

then converted to a fuzzy membership function

thus to perform a fuzzy comprehensive evaluation(FCE)on the satisfaction degree of the multi-variables to evaluate the laboratories' testing ability.Analysis on detection results of 34coal labs indicated that

the Z scorefuzzy comprehensive evaluation model can conduct an overall judgment and evaluation on labs

overcome the shortcoming that the RSA method can only deal with single factor problems and that the conventional methods have a large computational complexity

which can be applied in laboratory ability test with multi-factor set and multi-index set.

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