高技术企业生存风险预测模型的研究

The Forecasting Model of High-tech Enterprise Survival Risks

高技术企业在经营过程存在生存风险,预测高技术企业的生存风险,使企业能及时采取相应措施,是高技术企业保持可持续发展的有效途径。利用人工神经网络可以建立高技术企业生存风险预测模型,模型是利用BP神经网络误差反向传播学习算法建模,通过神经网络的学习来确定的,用效率、效益、结构类共13个指标作为生存风险评价指标体系,根据专家咨询及企业实地调查确定企业生存风险安全性数值范围;预测时只需把生存风险的指标数据输入模型,由模型计算出企业安全系数,通过企业安全系数来判断其生存风险。在实证研究中,通过样本企业的学习和检验确定预测模型,把待测的企业的指标数据输入模型计算出安全系数,实证表明,高技术企业生存风险预测模型具有较高的准确性。

There exist survival risks during the management process of high-tech enterprise.So it is an effective way to maintain the sustainable development to predict their existent risks and enable them to take corresponding measures.By use of the artificial nerve network people may establish the high-tech enterprise survival risk forecasting model.The model uses the BP nerve network error reverse dissemination study algorithm modeling,and determines through the nerve network study.The existent risk-predicting model is an indicator system evaluating the existent risk including efficiency,benefit,structure and so on,which judges the range of the corporation existent risks on the basis of quite a few experts and the corporation investigation.When forecasting people only need input the survival risk indication data,and calculate based on the model the enterprise safety coefficient,and then judges its survival risk through the enterprise safety coefficient.The existent risk-predicating model is confirmed through the learning and testing of corporations.And then input the indicator data of unmeasured corporations into the model and then calculate the corporation safety coefficient.The researches demonstrate that the existent risk-predicting model of the high-tech corporations has relatively high accuracy.