摘要
随着经济环境的复杂化和信息化水平的提高,企业对财务危机预警和诊断的有效性和智能化也越来越受到重视。基于SABNM的财务预警与诊断模型利用遗传算法搜索最优贝叶斯网络,利用其正向推理进行财务危机预警,利用逆向推理进行财务危机原因诊断,避免了统计方法的局限性和人工神经网络的不足。实验表明,SABNM预测模型准确率较高,且短期预测能力明显强于中长期预测能力,而SABNM诊断模型的原因诊断结果与实际资料也基本相符。
With the complex economic environment and increasing information level,enterprises are paying more and more attention to the effectiveness and intelligence of financial crisis warning and diagnosis.SABNM uses the genetic algorithm to search the optimal Bias network.By using the forward chained reasoning,we give a financial crisis warning,and by using backward chained reasoning,we make a financial crisis diagnosis,thus avoiding the limit of statistics and the deficiency of artificial nerve system.The experiment indicates that the predict model of SABNM is accurate and its short-term prediction is better that that of medium and long-term.Also,the result of diagnosis is basically in line with the actual result.
出处
《审计与经济研究》
CSSCI
北大核心
2013年第3期74-82,共9页
Journal of Audit & Economics
基金
国家自然科学基金面上项目(70972138)
中南财经政法大学融通型拔尖创新人才培养项目(2012RT09)
关键词
财务危机原因
企业财务预警
企业财务诊断
财务危机预警
贝叶斯网络模型
SABNM
reasons for financial crisis
enterprise financial warnings
enterprise financial diagnosis
financial crisis warnings
Bayesian Network Model
SABNM
