| 赵宇,张雨,范胜男,等.基于多重线性回归的航空飞行有效剂量估算模型建立[J].中华放射医学与防护杂志,2026,46(2):129-134.Zhao Yu,Zhang Yu,Fan Shengnan,et al.Development of flight personnel effective dose estimation model based on multiple linear regression[J].Chin J Radiol Med Prot,2026,46(2):129-134 |
| 基于多重线性回归的航空飞行有效剂量估算模型建立 |
| Development of flight personnel effective dose estimation model based on multiple linear regression |
| 投稿时间：2025-06-11 |
| DOI：10.3760/cma.j.cn112271-20250611-00199 |
| 中文关键词: 航空机组人员 职业照射 有效剂量 |
| 英文关键词:Aircrew Occupational exposure Effective dose |
| 基金项目: |
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| 中文摘要: |
| 目的 建立一套具有自主知识产权的、覆盖我国疆域的航空飞行有效剂量估算模型,实现航线辐射剂量的快速估算,助力我国航空机组人员职业健康管理体系的优化和完善。方法 用CARI-7A估算在国内已开放的696条航线在不同巡航高度下的14 616个飞行路径的有效剂量。将巡航时间、巡航高度、出发地经度、出发地纬度、目的地经度、目的地纬度作为自变量,航线有效剂量作为因变量,建立多重线性回归模型,并采用相关标准数据验证模型的准确性。结果 构建的多重线性回归模型R2adjusted为0.85,回归模型预测的航线有效剂量与国家标准提出的航线有效剂量的平均误差为7.0%。所有纳入模型的自变量中,巡航时间(β = 0.81,P < 0.05)是影响航空有效剂量的最主要因素,其次为巡航高度(β = 0.30,P < 0.05)、目的地纬度(β = 0.09,P < 0.05)和出发地纬度(β = 0.09,P < 0.05)。出发地经度和目的地经度分别表现出较弱的负相关关系(β = -0.02、 -0.03,P < 0.05)。所有变量均具有统计学意义,变量间未发现多重共线性(VIF < 5)。结论 构建的多重线性回归模型对航线有效剂量具有较好的估算能力,模型提示,在所有影响因素中,巡航时间和巡航高度均是影响航空飞行有效剂量的重要因素。此外,出发地和目的地的经纬度也对航空飞行中有效剂量有影响。航空公司可引入照射剂量这一因素,针对不同航线进行排班优化管理,合理可尽量降低航空机组人员宇宙射线照射剂量。 |
| 英文摘要: |
| Objective To develop a set of effective dose estimation models for flight personnel with independent intellectual property rights, which could be capable of covering the entire territory in the country and rapidly estimating radiation doses along flight routes and facilitating the optimization and improvement of the occupational health management system for Chinese aircrews. Methods Effective doses at different cruising altitudes were estimated using by CARI-7A simulation along 14 616 flight routes on 696 opened domestic routes. A multiple linear regression model was established with the flying time and altitude, longitude and latitude of departure location, and destination location as independent variables, and the effective dose on flight route as the dependent variable. Subsequently, the model was verified for accuracy by using relevant standard data. Results R2adjusted was 0.85 for the constructed multiple linear regression model and average error between the effective doses, predicted by regression model and proposed by the national standard, was 7.0%. Of all the independent variables introduced into the model, the flying time (β=0.81,P<0.05) was the primary factor influencing the effective dose to flight personnel, followed by altitude (β=0.30,P<0.05), destination latitude (β=0.09,P<0.05), and departure latitude (β=0.09,P<0.05). The departure longitude and the destination longitude exhibited relatively weak negative correlations (β=-0.02, -0.03, P<0.05). All variables were statistically significant, and no multicollinearity was detected among the variables (VIF< 5). Conclusions The constructed multiple linear regression model demonstrated a robust capability for estimating the effective dose on flight routes. The model revealed that of all influencing factors, both flying time and altitude were crucial factors influecing the effective dose during aviation. Additionally, the longitude and latitude of the departure and destination locations also have an influence on the effective dose during air travel. Airlines could take account of the factor of radiation exposure dose to optimize shift schedule management for different flight routes. This approach could reasonably minimize the cosmic radiation exposure to aircrew to the greatest extent possible. |
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