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Research on the credit classification of practicing qualification personnel in construction market based on self-organizing neural network

机译:基于自组织神经网络的建筑市场从业从业人员信用分类研究

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摘要

Combining with the characters of the practicing qualification personnel in construction market, evaluation method based on the self-organizing neural network is brought out to analyze the credit classification of the practicing qualification personnel. And the impact factors on the credit classification of the practicing qualification personnel, such as the number of neurons, the training steps, the dimension of neurons and the field of winning neurons are studied. Then a self-organizing competitive neural network is built. At last, a case study is conducted by taking practicing qualification personnel as an example. The research result reveals that the method can efficiently evaluate the credit of the practicing qualification personnel; thus, it could provide scientific advice to the construction enterprise to prevent relevant discreditable behaviors of some practicing qualification personnel.
机译:结合建筑市场从业人员的特点,提出了一种基于自组织神经网络的评估方法,对从业人员的信用分类进行了分析。并研究了影响从业资格人员资信分类的因素,如神经元数量,训练步骤,神经元大小和获胜神经元的领域。然后建立一个自组织的竞争神经网络。最后,以执业资格人员为例进行案例研究。研究结果表明,该方法可以有效地评价执业资格人员的信誉。因此,可以为建筑企业提供科学的建议,以防止某些执业资格人员的可耻行为。

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