基于支持向量机的环境γ剂量率模型  

Environmental γ Dose Rate Model Based on Support Vector Machine

作　　者：马元巍[1] 王德忠[1] 于文丹 朱月龙 张适[1] 

机构地区：[1]上海交通大学,上海200240 [2]核工业二四〇研究所,辽宁沈阳110032 [3]中核集团秦山核电有限公司,浙江海盐314300

出　　处：《原子能科学技术》2011年第11期1393-1398,共6页Atomic Energy Science and Technology

基　　金：教育部科技创新工程重大项目培育资金项目资助(708036)

摘　　要：核电厂外围环境辐射连续监测系统获取地表γ剂量率,当剂量率超过预先规定的阈值时,系统会发出警告。但氡子体影响、系统噪声造成的数值不稳定、剂量率具有周期性的变化均会使数据出现波动从而造成无效的报警。为辨别剂量率上升的原因,建立了支持向量机模型对环境剂量率超过阈值的原因进行分类,考察了不同参数对模型精度的影响。通过2 000组以上历史数据验证,结果表明,该模型能对环境γ剂量率超过阈值的原因进行准确分类,准确率达98%以上。The environment radiation monitoring system in nuclear power plant continuously monitors γ dose rate.If the dose rate exceeds a predetermined threshold,the system will issue a warning.However,the radon and thorium daughters effects and the system noise and their periodic changes will result in fake alarm.In order to study these factors,a support vector machine model was established to classify the reasons of threshold exceeding.The model was tested by more than 2 000 groups of historical data.The results show that it can accurately classify the reasons,and the accuracy rate is more than 98%.

关 键 词：Γ剂量率 降雨强度 支持向量机 分类 

分 类 号：X84[环境科学与工程—环境工程]