利用自组织神经网络技术，结合建筑市场执业资格人员信用的相关特点，研究了网络中神经元个数的确定、训练步数、网络维数、获胜神经元的领域等对网络结构和执业资格人员信用划分类别的影响，给出了执业资格人员信用分类的网络构造思想和神经网络结构，并以被调查的执业资格人员为例进行了实证研究。研究结果表明，该方法简便、易行，适用于执业资格人员信用分类研究，为开展执业资格人员信用管理奠定了良好的理论方法基础。

Combining with the characters of the practicing qualification personnel in construction market, evaluation method based on the self-organizing nerural 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 practicing qualification personnel.