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Realization and comparison of several regression algorithms for electron energy spectrum reconstruction

机译:几种电子能谱重建回归算法的实现与比较

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To determine the electron energy spectra for medical accelerator effectively, we investigate a nonlinear programming model with several nonlinear regression algorithms, including Levenberg-Marquardt, Quasi Newton, Gradient, Conjugate Gradient, Newton, Principal-Axis and NMinimize algorithms. The local relaxation-bound method is also developed to increase the calculation accuracy. The testing results demonstrate that the above methods could reconstruct the electron energy spectra effectively. Especially, further with the local relaxation-bound method the Levenberg-Marquardt, Newton and NMinimize algorithms could precisely obtain both the electron energy spectra and the photon contamination. Further study shows that ignoring about 4% photon contamination would increase error greatly, and it also inaccurately makes the electron energy spectra 'drift' to the low energy.
机译:为了有效地确定医用加速器的电子能谱,我们使用几种非线性回归算法研究了非线性规划模型,包括Levenberg-Marquardt,拟牛顿,梯度,共轭梯度,牛顿,主轴和NMinimize算法。还开发了局部松弛约束方法以提高计算精度。测试结果表明,以上方法可以有效地重建电子能谱。尤其是,进一步使用局部松弛约束方法,Levenberg-Marquardt,Newton和NMinimize算法可以精确地获得电子能谱和光子污染。进一步的研究表明,忽略约4%的光子污染会大大增加误差,并且还会使电子能谱“漂移”到低能。

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