基于HO-RF的大气透过率求解研究
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1.沈阳航空航天大学;2.中国航发沈阳发动机研究所

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基金项目:

国家自然科学基金项目(面上项目,重点项目,重大项目),


Study on the solution of atmospheric transmittance based on HO-RF
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Affiliation:

1.SHENYANG AEROSPACE UNIVERSITY;2.AECC Shenyang Engine Research Institute

Fund Project:

The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan)

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    摘要:

    为提升红外辐射测试中大气透过率参数的获取效率与精度,本研究提出了一种基于HO-RF算法的大气透过率求解模型。该模型以温度、湿度、作用距离和大气压等关键环境因素作为输入,结合实测数据建立回归求解模型,从而实现大气透过率的快速准确求解。仿真结果表明,相较于传统BP神经网络与RF模型,所提HO-RF模型在求解精度方面表现更优,均方根误差(RMSE)降低至0.010745,R2值为0.95877,平均绝对误差(MAE)为0.0080021。本研究提出的模型可有效降低实验操作复杂性,相较于传统方法具有更高精度、稳定性和可靠性,提高战机红外特性测试效率,具有良好的实际应用价值。

    Abstract:

    In order to improve the efficiency and accuracy of obtaining atmospheric transmittance parameters in infrared radiation test, this study proposes an atmospheric transmittance solution model based on HO-RF algorithm. The model takes the key environmental factors such as temperature, humidity, operating distance and atmospheric pressure as input, and establishes a regression solution model based on the measured data, so as to realize the rapid and accurate solution of atmospheric transmittance. The simulation results show that compared with the traditional BP neural network and RF model, the proposed HO-RF model performs better in terms of solution accuracy. The root mean square error ( RMSE ) is reduced to 0.010745, the R2 value is 0.95877, and the mean absolute error ( MAE ) is 0.0080021. The model proposed in this study can effectively reduce the complexity of experimental operation. Compared with the traditional method, it has higher accuracy, stability and reliability, and improves the efficiency of infrared characteristic test of fighter aircraft, which has good practical application value.

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