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首先构建了行业间中小企业信用评估指标体系,然后利用安徽省不同行业的800家中小企业调查数据,将其分为训练样本集和测试样本集,对BP神经网络的构造进行讨论,确定BP神经网络的算法,建立起基于BP神经网络的行业间信用评估模型,并代入2003年度全国农业和工业的部分分行业数据进行实证,并对仿真结果做出分析,指出造成农、工行业信用较大差距的原因,并提出加强农业行业信用建设的建议.
First of all, this paper constructs the index system of credit evaluation for SMEs in the industry. Then, using the survey data of 800 SMEs in different industries in Anhui Province, this paper divides them into training sample sets and test sample sets, and discusses the construction of BP neural network to determine the BP neural network Network, and establish a credit evaluation model based on BP neural network among industries, and put it into 2003 national agricultural and industrial part of the sub-sector data for empirical analysis of the simulation results, pointing out that the resulting agricultural and industrial credit The reason of the gap and put forward some proposals to strengthen the credit construction in agriculture industry.