The Levenberg-Marquardt (LM) algorithm is an iterative technique that locates the minimum of a function that is expressed as the sum of squares of nonlinear functions. It has become a standard technique for nonlinear least-squares problems and can be thought of as a combination of steepest descent and the Gauss-Newton method. This document briefly describes the mathematics behind levmar, a free...

The potential of the product unit neural networks built by using different memetic evolutionary algorithms for the simultaneous determination of mixtures of analytes based on dynamic responses was investigated. For this purpose, three methodologies for obtaining the structure and weights of neural networks were proposed, based on the combination of the evolutionary programming algorithm, a clus...

It is important to understand and forecast a typical or a particularly household daily consumption in order to design and size suitable renewable energy systems and energy storage. In this research for Short Term Load Forecasting (STLF) it has been used Artificial Neural Networks (ANN) and, despite the consumption unpredictability, it has been shown the possibility to forecast the electricity c...

The proliferation of inverter-based distributed energy resources (IBDERs) has increased the number control variables and dynamic interactions, leading to new grid challenges. For stability analysis designing appropriate protection controls, it is important that IBDER models are accurate. This paper focuses on accurate estimation parameter calibration DER_A, a recently proposed aggregated model....

In this paper, we consider nonlinear complementarity problem on management equilibrium model (NCP). To solve the problem, we first establish an error bound estimation for the NCP via a new type of residual function. Based on this, the famous Levenberg-Marquardt (L-M) algorithm is employed for obtaining its solution, and we show that the L-M algorithm is quadratically convergent without nondegen...

This paper presents a method for optimizing the parameters of Multilayer Perceptron Neural Networks (MLP NN) consisting of fuzzy flip-flops (F3) based on various operations using Bacterial Memetic Algorithm with the Modified Operator Execution Order (BMAM). In early work, the authors proposed the gradient based Levenberg-Marquardt (LM) algorithm for variable optimization. The BMAM local and glo...

The paper investigates a predictive control algorithm to regulate the output petroleum temperature of the tubular heat exchanger. In the controller design, a Takagi–Sugeno fuzzy model is applied in combination with the model predictive control algorithm. The process model in form of the Takagi–Sugeno fuzzy model is obtained via subtractive clustering from the plant's data set. The neural networ...