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Integration of BP Neural Network and Multistage Dynamic Fuzzy Evaluation and Its Application in HRM Performance Measurement

机译:BP神经网络与多级动态模糊评价的集成及其在HRM性能测量中的应用

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Human resources management (HRM) is very important for the enterprises'' existence and development, but how to measure the HRM performance is a major issue that troubled the enterprises. This paper overcomes the shortcoming of tradition linear HRM evaluation method, proposes a evaluation method which unifies the BP neural network algorithm and the multistage dynamic fuzzy judgment, takes the multistage dynamic fuzzy judgment as the sampling foundation, uses the BP neural network principle to establish evaluation model. This method not only can exert the unique advantages of BP neural network, but also overcome the difficulty of seeking the high grade training sample data. The HRM performance evaluation of 10 enterprises, indicates that the method to evaluate the HRM is stable and reliable.
机译:人力资源管理(HRM)对企业的存在和发展非常重要,但如何衡量人力资源管理资源管理资源生产力问题是企业陷入困境的主要问题。本文克服了传统线性HRM评估方法的缺点,提出了一种评价方法,统一BP神经网络算法和多级动态模糊判断,采用多级动态模糊判断作为采样基础,采用BP神经网络原理建立评估模型。这种方法不仅可以施加BP神经网络的独特优势,还克服了寻求高档训练样本数据的难度。 10家企业的HRM性能评估表明,评估HRM的方法是稳定可靠的。

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