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首页> 外文会议>International Conference on Management Science Engineering >A group method of symmetric triangular fuzzy numbers handling and its application to analyze monitoring data of small and micro enterprises in Sichuan Province
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A group method of symmetric triangular fuzzy numbers handling and its application to analyze monitoring data of small and micro enterprises in Sichuan Province

机译：对称三角模糊数处理的组方法及其在四川省小微企业监测数据分析中的应用

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摘要

Group method of data handling has been proven an effective knowledge mining tool to emerge the influencing factors of enterprises growth in the past researches, but when employed to analyze the small and micro enterprises in Sichuan Province, its effectiveness is reduced by the noise in the data obtained from the enterprises' produce and business operations monitor platform website. In order to increase the noise immunity of the method, the monitoring data is firstly processed as some symmetric triangular fuzzy numbers in this paper, and the parameter estimation technique for all self-organized models named partial functions in the method is changed from the former regression analysis with determined training data set to the fuzzy programming with fuzzy set. Basing on this transform, a group method of the symmetric triangular fuzzy numbers handling is presented and the result of its empirical study in Sichuan Province proves the method is able to disclose some key influencing factors of the small and micro enterprises' growth with unstable and noisy monitoring data.
机译：在过去的研究中，数据处理的分组方法已被证明是一种有效的知识挖掘工具，它可以显示出影响企业成长的因素，但是当用于分析四川省的小型和微型企业时，其有效性会由于数据中的噪声而降低。从企业的生产和经营监控平台网站获得。为了提高该方法的抗干扰能力，本文首先将监测数据处理为一些对称的三角模糊数，并将该方法中所有名为偏函数的自组织模型的参数估计技术从原来的回归方法进行了改变。将确定的训练数据集进行分析，再将模糊集进行模糊规划。在此变换的基础上，提出了一种对称三角模糊数处理的方法，并在四川省进行了实证研究，结果表明该方法能够揭示不稳定，嘈杂的小微企业成长的一些关键影响因素。监控数据。

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