CAJ | 학술논문

针对当下航空公司安全质量管理体系（ Quality Management System，SQMS）中风险识别与可靠性改进的问题，提出了基于区间数学改进的贝叶斯神经网络的灵敏度分析方法。利用区间数学理论分析贝叶斯神经网络中各指标与整体安全质量状况的扰动关系，实现指标灵敏度分析。通过东方航空公司的实例分析，发现在对指标进行人工干预时组合指标干预效果较好，且安全管理体系实施后指标的灵敏度有明显向好的方向变化的趋势。
침대당하항공공사안전질량관리체계（ Quality Management System，SQMS）중풍험식별여가고성개진적문제，제출료기우구간수학개진적패협사신경망락적령민도분석방법。이용구간수학이론분석패협사신경망락중각지표여정체안전질량상황적우동관계，실현지표령민도분석。통과동방항공공사적실례분석，발현재대지표진행인공간예시조합지표간예효과교호，차안전관리체계실시후지표적령민도유명현향호적방향변화적추세。
To meet the requirements of risk identification and reliability improvement on Safety and Quality Manage-ment System ( SQMS) in airline companies, a method of sensitivity analysis by improved Bayesian neural network based on interval mathematics was put forward.The interval mathematics theory was applied to analyze the disturb-ance relationship between each index and overall safety and quality status of Bayesian neural network, so as to real-ize the sensitivity analysis of indexes.The case study of Eastern Airlines showed that the intervention effect of com-bined indexes was better when conducting artificial intervention to indexes, and the sensitivity of indexes tended to be better obviously after the implementation of safety management system.