基于人工神经网络的企业生产预警管理系统研究

Research of enterprise production early-warning management system based on artificial neural network

企业生产预警管理是生产企业现代管理的一种新模式,它通过监测指标,对企业外部环境变化和生产管理活动进行综合评价,判断企业生产管理所处状态,并采取相应的预先控制对策,使企业生产管理活动始终处于“安全、有效”的管理模式。人工神经网络是广泛应用于众多学科的非线性模拟技术,文章将人工神经网络技术应用到企业生产预警管理中,根据影响生产管理的指标和分类标准随机生成有效的样本数据以建立人工神经网络模型。结果表明样本生成方法和应用人工神经网络技术进行企业生产预警管理评估的方法是合理并可行的。

Enterprise production early-warning management system （EPEMS） is a new approach for modem management. Some monitor indexes was established and applied to comprehensively assess the enterprise exterior environment and production management and taking pre,control measures to guarantee enterprise production operation activity in a ＂safety and effective＂ mode by judging the enterprise production management condition. Artificial neural network （ANN）, with excellent nonlinear approximation ability, is widely applied successfully in many fields and thus used for EPEMS in this paper. According to the indexes and classification criteria influencing enterprise production management, the random distributing theory was used to produce efficient sample data, used in setting up neural network model. The ease study shown that the method of producing samples and the EPEMS comprehensive assessment model based on ANN were reasonable and feasible.