Abstract The Levenberg–Marquardt method is a fundamental regularization technique for
the Newton method applied to nonlinear equations, possibly constrained, and possibly with …

In this paper, an ensemble learning approach is proposed for load forecasting in urban
power systems. The proposed framework consists of two levels of learners that integrate …

We develop a framework for a class of derivative-free algorithms for the least-squares
minimization problem. These algorithms are designed to take advantage of the problem …

This paper presents a nonlinear transfer function noise model for time‐series modeling of
unconfined groundwater hydrographs. The motivation for its development was that existing …

In this paper, a novel fuzzy neural network with intuitive, interpretable, and correlated-
contours fuzzy rules (IC-FNN), for function approximation, is presented. The surfaces of …

Parameter estimation is an inverse problem which is crucial to reliable groundwater model
predictions and management. Numerous techniques have been developed to address this …

In [C. Ma, L. Jiang, Some research on Levenberg–Marquardt method for the nonlinear
equations, Appl. Math. Comput. 184 (2007) 1032–1040], the LM parameter at the kth …

Abstract The modified Levenberg–Marquardt (MLM) method to solve nonlinear equations
was introduced by Fan (2012). This method uses an addition of the Levenberg–Marquardt …

It is crucial to have precise and current maps of aboveground biomass (AGB) in boreal
forests to accurately track global carbon levels and develop effective plans for addressing …

In this paper we propose an accelerated version of the modified Levenberg-Marquardt
method for nonlinear equations (see **yan Fan, Mathematics of Computation 81 (2012), no …