摘要
将人工神经网络应用于高校实验室安全评价中,提出一种基于BP神经网络的高校实验室安全评价模型。参考国内实验室安全评价的研究成果,结合福州大学实验室的特点,建立高校实验室安全评价指标体系。该模型将实验室安全评价指标量化为具体的数据作为BP网络的输入,评价结果作为输出。通过专家评分获得训练样本,用trainlm函数训练网络,并对测试数据进行网络仿真。实验表明网络仿真训练值与实际评价结果误差很小,验证了该评价模型的适用性。该模型可以利用已有较成功的实验室安全评价案例信息,使专家的评价经验得到积累,为实验室安全评价提供较科学的量化标准。
The evaluation model of university laboratory safety based on BP neural network is presented. By reference of the domestic research for laboratory safety evaluation and combining with of laboratory characteristics of Fuzhou University, the safety evaluation index system of university laboratory is selected. This model quantifies the evaluation index of laboratory safety into definite data as the input for BP network, and taking it output as the evaluation results. The BP network is trained by Trainlm function with training samples which have been obtained by experts, and then it is simulated with testing data. The experiments show that the error between the training value of network simulation and the actual evaluation results is very small, then the applicability of the evaluation model is illustrated. The existing information of laboratory safety evaluation with relatively successful cases can be used in the model, hence the experience of experts can be accumulated for providing more scientific and quantitative criteria for the laboratory safety evaluation.
出处
《实验室研究与探索》
CAS
北大核心
2013年第2期214-218,共5页
Research and Exploration In Laboratory
基金
福州大学第五批"高等教育教学改革工程"立项项目(036375)
关键词
高校实验室
实验室安全
BP神经网络
评价模型
评价指标
university laboratory
laboratory safety
BP neural network
evaluation model
evaluation index