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一種求解非線性方程組的修正Levenberg-Marquardt算法

2023-06-23 17:28:50韓揚芮紹平
青島大學學報(自然科學版) 2023年1期

韓揚 芮紹平

摘要:通過修改Levenberg-Marquardt (LM)參數,結合信賴域方法給出一種新的求解方程組的LM算法。在局部誤差界條件下,證明了該算法具有局部快速收斂性。數值實驗結果表明,此算法穩定、有效。

關鍵詞:Levenberg-Marquardt算法;方程組;LM參數;局部快速收斂性

中圖分類號:O221.1 文獻標志碼:A

從表1中的數值實驗結果可以看出,ALLM算法相對穩定,對于大部分測試的實驗結果,ALLM算法的計算時間小于AELM算法的計算時間,并且當選取的初始點遠離解集時,算例3在參數θ=05及δ=2、算例5在參數θ=05及δ=15,2和算例9在參數θ=05及δ=1,15,2時,ALLM算法的計算量和計算時間均小于AELM算法。

4 結論

本文結合信賴域方法提出了一種求解非線性方程組的修正的LM算法(ALLM算法),在不必假設雅可比矩陣非奇異的局部誤差界條件下,證明了該算法具有局部快速收斂性。可根據實際應用的需要,通過改變θ和δ值以優化λk的選取,數值實驗結果表明,ALLM算法穩定有效。然而雅可比矩陣的計算量和收斂速度還需繼續改善,如何節約雅可比矩陣的計算量和提升收斂速度是今后有待解決的問題。

參考文獻

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Modified Levenberg-Marquardt Algorithm for Solving Systems of Nonlinear Equations

HAN Yang,RUI Shao-ping

(School of Mathematical Sciences, Huaibei Normal University, Huaibei 235000, China)

Abstract: A new modified Levenberg-Marquardt (LM) algorithm for solving systems of equations was presented by modifying Levenberg-Marquardt (LM) parameters and combining trust region method. Under the local error bound condition, it was proved that the algorithm has local fast convergence. Numerical results show that this algorithm is stable and effective.

Keywords: Levenberg-Marquardt algorithm; systems of equations; LM parameter; local fast convergence

收稿日期:2022-09-24

基金項目:安徽省高等學校自然科學研究項目(批準號:KJ2020A0024)資助;淮北師范大學實驗室開放項目(批準號:2022sykf016)資助。

通信作者:芮紹平,男,博士,教授,主要研究方向為最優化理論與算法。E-mail:rsp9999@163.com

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