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...

The designing of advanced driver assistance systems and autonomous vehicles needs measurement of dynamical variations of vehicle, such as acceleration, velocity and yaw rate. Designed adaptive controllers to control lateral and longitudinal vehicle dynamics are based on the measured variables. Inertial MEMS-based sensors have some benefits including low price and low consumption that make them ...

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...

Abstract—Levenberg-Marquardt method (LM) was proposed to be applied as a non-linear least-square fitting in the analysis of a natural gamma-ray spectrum that was taken by the Hp (Ge) detector. The Gaussian function that composed of three components, main Gaussian, a step background function and tailing function in the lowenergy side, has been suggested to describe each of the -ray lines mathem...

Resumen: En este trabajo se presentan los resultados experimentales del control neuronal de velocidad de un servosistema. La estrategia de control neuronal implementada es el control por modelo inverso. El entrenamiento de la red se ha realizado usando dos algoritmos de aprendizaje: Levenberg-Marquardt y regularización Bayesiana. Se evalúa la capacidad de generalización de cada método en funció...

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....

The aim of this study was to estimate suspended sediment by the ANN model, DT with CART algorithm and different types of SRC, in ten stations from the Lorestan Province of Iran. The results showed that the accuracy of ANN with Levenberg-Marquardt back propagation algorithm is more than the two other models, especially in high discharges. Comparison of different intervals in models showed that r...