Relevant bibliographies by topics / Levenberg Marquardt method

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  2. Dissertations / Theses
  3. Books
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Academic literature on the topic 'Levenberg Marquardt method'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Levenberg Marquardt method"

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Wu, Zhenxiang, Tong Zhou, Lei Li, Liang Chen, and Yanfang Ma. "A New Modified Efficient Levenberg–Marquardt Method for Solving Systems of Nonlinear Equations." Mathematical Problems in Engineering 2021 (August 31, 2021): 1–11. http://dx.doi.org/10.1155/2021/5608195.

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For systems of nonlinear equations, a modified efficient Levenberg–Marquardt method with new LM parameters was developed by Amini et al. (2018). The convergence of the method was proved under the local error bound condition. In order to enhance this method, using nonmonotone technique, we propose a new Levenberg–Marquardt parameter in this paper. The convergence of the new Levenberg–Marquardt method is shown to be at least superlinear, and numerical experiments show that the new Levenberg–Marquardt algorithm can solve systems of nonlinear equations effectively.
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Izmailov, Alexey, Alexey Kurennoy, and Petr Stetsyuk. "Levenberg–Marquardt method for unconstrained optimization." Tambov University Reports. Series: Natural and Technical Sciences, no. 125 (2019): 60–74. http://dx.doi.org/10.20310/1810-0198-2019-24-125-60-74.

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We propose and study the Levenberg–Marquardt method globalized by means of linesearch for unconstrained optimization problems with possibly nonisolated solutions. It is well-recognized that this method is an efficient tool for solving systems of nonlinear equations, especially in the presence of singular and even nonisolated solutions. Customary globalization strategies for the Levenberg–Marquardt method rely on linesearch for the squared Euclidean residual of the equation being solved. In case of unconstrained optimization problem, this equation is formed by putting the gradient of the object
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He, Zhi, Lan Yun Li, and Yong Qin Liu. "Calculating the Phase Equilibria of Al Rich Al-Cu-Mg Alloys." Advanced Materials Research 287-290 (July 2011): 2411–14. http://dx.doi.org/10.4028/www.scientific.net/amr.287-290.2411.

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This paper investigates a new method, the Levenberg-Marquardt method, to calculate the phase equilibria of the Al-Cu-Mg ternary alloys. The Levenberg-Marquardt method is the best algorithm to obtain the least-square solution of non-linear equations. Its application to ternary Al-Cu-Mg system is executed in detail in this paper. The calculated phase equilibria agrees well with the experimental results. Furthermore, the Levenberg-Marquardt method is not sensitive to the initial values.
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Chen, Liang, and Yanfang Ma. "A New Modified Levenberg–Marquardt Method for Systems of Nonlinear Equations." Journal of Mathematics 2023 (February 10, 2023): 1–13. http://dx.doi.org/10.1155/2023/6043780.

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Taking a new choice of the LM parameter λ k = μ k J k T F k δ with δ ∈ 0,2 , we give a new modified Levenberg–Marquardt method. Under the error bound condition c dist w , S ≤ J w T F w which is weaker than the nonsingular of Jacobian J w , we present that the new Levenberg–Marquardt method has at least superlinear convergence when δ ∈ 0,1 and quadratic convergence when δ ∈ 1,2 , respectively, which indicates that our new Levenberg–Marquardt method is performed for the systems of nonlinear equations. Also, numerical experiments indicate its efficiency on a set of systems of nonlinear equations.
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Cho, Kar Mun, Nur Haizum Abd Rahman, and Iszuanie Syafidza Che Ilias. "Performance of Levenberg-Marquardt Neural Network Algorithm in Air Quality Forecasting." Sains Malaysiana 51, no. 8 (2021): 2645–54. http://dx.doi.org/10.17576/jsm-2022-5108-23.

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Levenberg-Marquardt algorithm and conjugate gradient method are frequently used for optimization in multi-layer perceptron (MLP). However, both algorithms have mixed conclusions in optimizing MLP in time series forecasting. This study uses autoregressive integrated moving average (ARIMA) and MLP with both Levenberg-Marquardt algorithm and conjugate gradient method. These methods were used to predict the Air Pollutant Index (API) in Malaysia's central region where represent urban and residential areas. The performances were discussed and compared using the mean square error (MSE) and mean absol
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Izmailov, Alexey F., and Evgeniy I. Uskov. "Hybrid globalization of convergence of the Levenberg-Marquardt method for equality-constrained optimization problems." Russian Universities Reports. Mathematics, no. 149 (2025): 41–55. https://doi.org/10.20310/2686-9667-2025-30-149-41-55.

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The Levenberg-Marquardt method possesses local superlinear convergence for general systems of nonlinear equations under weal assumptions allowing for nonisolated solutions. This justifies its application to first-order optimality systems of constrained optimization problems with possibly violated constraint qualifications, the latter giving rise to nonuniqueness of Lagrange multipliers. However, the existing strategies for globalization of convergence of the Levenberg-Marquardt method are not optimization-oriented by nature, i.e., when applied to optimization problems, they are intended not fo
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Du, Shou-qiang, and Yan Gao. "A Modified Levenberg-Marquardt Method for Nonsmooth Equations with Finitely Many Maximum Functions." Mathematical Problems in Engineering 2008 (2008): 1–10. http://dx.doi.org/10.1155/2008/942391.

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For solving nonsmooth systems of equations, the Levenberg-Marquardt method and its variants are of particular importance because of their locally fast convergent rates. Finitely many maximum functions systems are very useful in the study of nonlinear complementarity problems, variational inequality problems, Karush-Kuhn-Tucker systems of nonlinear programming problems, and many problems in mechanics and engineering. In this paper, we present a modified Levenberg-Marquardt method for nonsmooth equations with finitely many maximum functions. Under mild assumptions, the present method is shown to
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Fan, Jinyan, and Jianyu Pan. "Inexact Levenberg-Marquardt method for nonlinear equations." Discrete & Continuous Dynamical Systems - B 4, no. 4 (2004): 1223–32. http://dx.doi.org/10.3934/dcdsb.2004.4.1223.

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Fan, Jinyan, Jianchao Huang, and Jianyu Pan. "An Adaptive Multi-step Levenberg–Marquardt Method." Journal of Scientific Computing 78, no. 1 (2018): 531–48. http://dx.doi.org/10.1007/s10915-018-0777-8.

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Zhang, Ju-liang, and Xiangsun Zhang. "A smoothing Levenberg–Marquardt method for NCP." Applied Mathematics and Computation 178, no. 2 (2006): 212–28. http://dx.doi.org/10.1016/j.amc.2005.11.036.

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Dissertations / Theses on the topic "Levenberg Marquardt method"

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Shan, Shidong. "A Levenberg-Marquardt method for large-scale bound-constrained nonlinear least-squares." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/5648.

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The well known Levenberg-Marquardt method is used extensively for solving nonlinear least-squares problems. We describe an extension of the Levenberg- Marquardt method to problems with bound constraints on the variables. Each iteration of our algorithm approximately solves a linear least-squares problem subject to the original bound constraints. Our approach is especially suited to large-scale problems whose functions are expensive to compute; only matrix-vector products with the Jacobian are required. We present the results of numerical experiments that illustrate the effectiveness of the app
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Araneda, Evelyn 1974. "A variation of the Levenberg Marquardt method : an attempt to improve efficiency." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/28609.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, June 2004.<br>"May 2004."<br>Includes bibliographical references (leaf 36).<br>The Levenberg-Marquardt method is an efficient and popular damped least square technique. This method is a combination between the Gauss and the steepest gradient descent methods, where the amount of damping used in each iteration is central in establishing the behavior of the system. Further, the damping is determined by four parameters, whose optimum values vary from model to model. An inappropriate selection
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Pitra, Michal. "Adaptivní regulátory s principy umělé inteligence v prostředí MATLAB - B&R." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2008. http://www.nusl.cz/ntk/nusl-217708.

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The diploma thesis is focused on an adaptive control, especially in a self-tuning controller area. The thesis is divided into two main parts. The first part deals with identification methods of the adaptive control. The recursive least squares algorithm and the neural network method are the most popular identification methods. These methods are contrasted and the identification quality evaluation is done. The second part compares various types of the adaptive controllers with a non-adjustable PSD controller. The adaptive controllers are investigated from the various identification method point
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Peters, Franciane Conceição. "Estratégia para a solução numérica do problema inverso da identificação de inclusões em domínio condutor." Universidade Federal de Juiz de Fora (UFJF), 2010. https://repositorio.ufjf.br/jspui/handle/ufjf/3481.

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Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-02-23T19:26:50Z No. of bitstreams: 1 francianeconceicaopeters.pdf: 4730497 bytes, checksum: 201c60342a8bf9edc9b308fa50fafa54 (MD5)<br>Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-02-24T12:08:43Z (GMT) No. of bitstreams: 1 francianeconceicaopeters.pdf: 4730497 bytes, checksum: 201c60342a8bf9edc9b308fa50fafa54 (MD5)<br>Made available in DSpace on 2017-02-24T12:08:43Z (GMT). No. of bitstreams: 1 francianeconceicaopeters.pdf: 4730497 bytes, checksum: 201c60342a8bf9edc9b308fa50fafa54 (MD5)
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Unnikrishnakurup, Sreedhar. "Etude expérimentale et numérique d'un essai de soudage TIG statique et estimation des paramètres du flux de chaleur." Thesis, Montpellier 2, 2014. http://www.theses.fr/2014MON20013/document.

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Le procédé de soudage à l'arc sous atmosphère inerte (TIG) est souvent employé pour des assemblages nécessitant une grande qualité du joint soudé. Les propriétés du joint soudé dépendent essentiellement du cycle thermique imposé par l'opération de soudage, de la composition chimique du matériau métallique et des mouvements convectifs du métal fondu dans le bain de fusion. L'écoulement du métal liquide dans le bain de fusion modifie la distribution de température en son sein et à proximité, ainsi que la forme géométrique du joint. Afin d'améliorer l'opération de soudage TIG, par exemple pour ac
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Abbas, Boushra. "Méthode de Newton régularisée pour les inclusions monotones structurées : étude des dynamiques et algorithmes associés." Thesis, Montpellier, 2015. http://www.theses.fr/2015MONTS250/document.

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Cette thèse est consacrée à la recherche des zéros d'un opérateur maximal monotone structuré, à l'aide de systèmes dynamiques dissipatifs continus et discrets. Les solutions sont obtenues comme limites des trajectoires lorsque le temps t tend vers l'infini. On s'intéressera principalement aux dynamiques obtenues par régularisation de type Levenberg-Marquardt de la méthode de Newton. On décrira aussi les approches basées sur des dynamiques voisines.Dans un cadre Hilbertien, on s'intéresse à la recherche des zéros de l'opérateur maximal monotone structuré M = A + B, où A est un opérateur maximal
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Herrich, Markus. "Local Convergence of Newton-type Methods for Nonsmooth Constrained Equations and Applications." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-159569.

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In this thesis we consider constrained systems of equations. The focus is on local Newton-type methods for the solution of constrained systems which converge locally quadratically under mild assumptions implying neither local uniqueness of solutions nor differentiability of the equation function at solutions. The first aim of this thesis is to improve existing local convergence results of the constrained Levenberg-Marquardt method. To this end, we describe a general Newton-type algorithm. Then we prove local quadratic convergence of this general algorithm under the same four assumptions which
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Mrázek, Michal. "Adaptivní optimální regulátory s principy umělé inteligence v prostředí MATLAB - B&R." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2008. http://www.nusl.cz/ntk/nusl-217556.

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Master’s thesis describes adaptive optimal controller design which change parameters of algorithm based on the system information regard for optimal criterion. Generally, the optimal controller solves the problem of minimum states vector. Problems of desired value and steady-state error are solved by variation in optimization algorithm.
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Samek, Martin. "Adaptivní optimální regulátory s principy umělé inteligence v prostředí MATLAB - B&R." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-218211.

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Master’s thesis describes adaptive optimal controller design and it’s settings. Identification with principles of artificial intelligence and recursive least squares identification with exponential and directional forgetting are compared separately and as part of controller. Adaptive optimal controller is tested on physical model and compared with solidly adjusted PSD controller. Possibilities of implementation of adaptive optimal controller into programmable logic controller B&R are show and tested.
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Ribeiro, Marcos Henrique Fonseca. "Modelos computacionais para simulações de tomografia por impedância elétrica e sua aplicação no problema de determinação da fração de ejeção cardíaca". Universidade Federal de Juiz de Fora (UFJF), 2016. https://repositorio.ufjf.br/jspui/handle/ufjf/4509.

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Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-05-15T14:59:59Z No. of bitstreams: 1 marcoshenriquefonsecaribeiro.pdf: 12873424 bytes, checksum: 2b2b91fd2a9726856a0486afa760fe2c (MD5)<br>Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-05-17T16:01:12Z (GMT) No. of bitstreams: 1 marcoshenriquefonsecaribeiro.pdf: 12873424 bytes, checksum: 2b2b91fd2a9726856a0486afa760fe2c (MD5)<br>Made available in DSpace on 2017-05-17T16:01:12Z (GMT). No. of bitstreams: 1 marcoshenriquefonsecaribeiro.pdf: 12873424 bytes, checksum: 2b2b91fd2a9726856a0486afa7
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Books on the topic "Levenberg Marquardt method"

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Chance, Kelly, and Randall V. Martin. Data Fitting. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199662104.003.0011.

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This chapter explores several of the most common and useful approaches to atmospheric data fitting as well as the process of using air mass factors to produce vertical atmospheric column abundances from line-of-sight slant columns determined by data fitting. An atmospheric spectrum or other type of atmospheric sounding is usually fitted to a parameterized physical model by minimizing a cost function, usually chi-squared. Linear fitting, when the model of the measurements is linear in the model parameters is described, followed by the more common nonlinear fitting case. For nonlinear fitting, t
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Book chapters on the topic "Levenberg Marquardt method"

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Murthy, Z. V. P. "Nonlinear Regression: Levenberg-Marquardt Method." In Encyclopedia of Membranes. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-40872-4_1656-1.

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Baig, Maughal Ahmed Ali, Mudimela Madhusudhan, Sayyad Rasheeduddin, V. Sravani Kumar, Borra Sivaiah, and K. Venkateswara Rao. "Levenberg Marquardt Method for Optimized Clustering of Data Mining." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-81083-1_42.

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Yamashita, N., and M. Fukushima. "On the Rate of Convergence of the Levenberg-Marquardt Method." In Topics in Numerical Analysis. Springer Vienna, 2001. http://dx.doi.org/10.1007/978-3-7091-6217-0_18.

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Nguyen, Q., S. Nguyen-Hoai, T. Chuong-Thiet, and T. Lam-Phat. "Optimization of the Longitudinal Cooling Fin by Levenberg–Marquardt Method." In Proceedings of the International Conference on Advances in Computational Mechanics 2017. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7149-2_15.

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Irwansyah, E., Rian Budi Lukmanto, Rokhana D. Bekti, and Priscilia Budiman. "Computer-Based Ground Motion Attenuation Modeling Using Levenberg-Marquardt Method." In Automation Control Theory Perspectives in Intelligent Systems. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33389-2_28.

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Fang, Minglei, Feng Xu, Zhibin Zhu, Lihua Jiang, and Xianya Geng. "On the Convergence of Levenberg-Marquardt Method for Solving Nonlinear Systems." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-45049-9_19.

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Irwansyah, Edy, Bayu Kanigoro, Priscilia Budiman, and Rokhana D. Bekti. "Earthquake Ground Motion Attenuation Modeling Using Levenberg-Marquardt and Brute-Force Method." In Applied Computational Intelligence and Mathematical Methods. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67621-0_26.

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Tho, Tran Quang, Pham Huu Ly, Truong Viet Anh, and Le Minh Phuong. "A Synchronization Method for Three-Phase Grid-Connected Inverters Using Levenberg-Marquardt Technique." In AETA 2015: Recent Advances in Electrical Engineering and Related Sciences. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27247-4_22.

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Dkhichi, Fayrouz. "Parametric Identification by Improved Levenberg-Marquardt Method of Solar Cell’s Double Diode Model." In Digital Technologies and Applications. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-01942-5_68.

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Burachik, Regina S., and C. Yalçın Kaya. "Visualization of Convergence Behavior of a Generalized Newton Method and Levenberg–Marquardt Algorithm." In Handbook of Visual, Experimental and Computational Mathematics. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-030-93954-0_16-1.

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Conference papers on the topic "Levenberg Marquardt method"

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Chen, Mao, Juan Chen, and Chunhui Mou. "Dispersion data fitting based on Levenberg-Marquardt data fitting method." In 2024 International Applied Computational Electromagnetics Society Symposium (ACES-China). IEEE, 2024. http://dx.doi.org/10.1109/aces-china62474.2024.10699849.

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Radler, Simon, and Manfred Hajek. "Periodic Free Wake Simulation Using a Numerical Optimization Method." In Vertical Flight Society 72nd Annual Forum & Technology Display. The Vertical Flight Society, 2016. http://dx.doi.org/10.4050/f-0072-2016-11373.

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A novel method has been developed for the free vortex wake simulation of rotors under the assumption of periodicity. An error measure is introduced which is based on the mismatch between prevailing convection velocities and the assumed wake element positions. The systematic reduction of this defined error results in a numerically robust method for the computation of wake geometries. Two strategies are compared for the error reduction. The first uses the repeated evaluation of the velocity field to update the wake geometry as long as the defined error decreases. In the second strategy, the appl
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Wang, Quan, Wei Xu, Wenlong Li, and Han Ding. "A Novel Robot Positioning Accuracy Calibration Method Integrating Levenberg-Marquardt and Differential Evolution Algorithm." In 2024 3rd International Conference on Artificial Intelligence and Computer Information Technology (AICIT). IEEE, 2024. http://dx.doi.org/10.1109/aicit62434.2024.10730526.

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Durga, P. Lakshmi, and Sukanta Nayak. "Modified Levenberg-Marquardt Neural Network Method to Investigate Optimum Height of a Water Tank Problem." In 2024 OITS International Conference on Information Technology (OCIT). IEEE, 2024. https://doi.org/10.1109/ocit65031.2024.00066.

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Krause, Caroline, and Stephan Frei. "Application of Levenberg-Marquardt Method for Optimizing Gate Driving Signals of a DC/DC Converter to Reduce Switching Resonances." In 2024 International Symposium on Electromagnetic Compatibility – EMC Europe. IEEE, 2024. http://dx.doi.org/10.1109/emceurope59828.2024.10722697.

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Wang, Jiaxuan, Yinsheng Su, Guanghu Xu, et al. "A Novel Constrained Load Flow Model and Algorithm for New-Type Power System Based on the Levenberg-Marquardt Method." In 2024 8th International Conference on Power and Energy Engineering (ICPEE). IEEE, 2024. https://doi.org/10.1109/icpee64457.2024.10949980.

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Yu, Zhuojun, Zhiping Liao, Hongjun Shi, and Yao Chen. "An Innovative Method for the State of Charge Estimation Utilizing an Enhanced Firework Algorithm and Levenberg-Marquardt Optimization Neural Network." In 2025 2nd International Conference on Smart Grid and Artificial Intelligence (SGAI). IEEE, 2025. https://doi.org/10.1109/sgai64825.2025.11009573.

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Sajedi, Ramin, Javad Faraji, Forooza Samadi, and Farshad Kowsary. "Adaptive Determination of the Damping Coefficient of the Levenberg-Marquardt Algorithm Using Type-2 Fuzzy in Inverse Heat Transfer Problems." In ASME 2024 Heat Transfer Summer Conference collocated with the ASME 2024 Fluids Engineering Division Summer Meeting and the ASME 2024 18th International Conference on Energy Sustainability. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/ht2024-137041.

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Abstract In this study, a combination of the Levenberg-Marquardt algorithm and the type-2 fuzzy method is used to solve an inverse heat transfer problem. Considering the essential role of the damping factor in the stability and efficiency of the Levenberg-Marquardt algorithm in solving ill-posed problems, a new method based on fuzzy logic theory is used to update the value of this parameter in the iteration of the solution. A cubic polynomial test case is estimated using classical, type-1, and type-2 fuzzy Levenberg-Marquardt methods for the boundary heat flux in a one-dimensional heat transfe
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Durdağ, D. "Using Levenberg–Marquardt Method In Dispersion Curve Fitting." In 9th Congress of the Balkan Geophysical Society. EAGE Publications BV, 2017. http://dx.doi.org/10.3997/2214-4609.201702594.

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Chauhan, Vinod Kumar, Kalpana Dahiya, and Anuj Sharma. "Trust Region Levenberg-Marquardt Method for Linear SVM." In 2017 Ninth International Conference on Advances in Pattern Recognition (ICAPR). IEEE, 2017. http://dx.doi.org/10.1109/icapr.2017.8593090.

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Reports on the topic "Levenberg Marquardt method"

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Bledsoe, Keith, Jordan Lefebvre, and David Hooper. Samoa Updater: An Application of the Levenberg-Marquardt Method to Update Delfic Predictions Using Field Measurements. Office of Scientific and Technical Information (OSTI), 2024. http://dx.doi.org/10.2172/2397438.

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