Objetivo. Este artículo muestra el diseño y entrenamiento de una red neuronal artificial (RNA) para predecir resultados académicos estudiantes Ingeniería Civil la Universidad Nacional Intercultural Fabiola Salazar Leguía Bagua-Perú en asignatura Matemática II. Método. Se utilizó metodología CRISP-DM, recolectar los datos se emplearon encuestas, modelo RNA implementó software Matlab utilizando c...

This paper describes the efficient MPPT tracking for variable wind speed using an artificial neural network. The network has been trained backpropagation algorithm and Levenberg-Marquardt (LM) based optimization technique to achieve maximum power point. A multilevel inverter having 10 switches used reduce voltage stress, THD switching losses resulting in improvement performance reduction driver...

In this paper, we develop a novel method for camera calibration and correction. The novel method first employs a rigidity constraint from the rigid rotation matrix and the radial alignment constraint from the pin-hole camera model to estimate both camera intrinsic and extrinsic parameters with a closed-form solution without considering the camera distortion. Then the well-known Levernburg-Marqu...

The stability of power production in photovoltaics (PV) power plants is an important issue for large-scale gridconnected systems. This is because it affects the control and operation of the electrical grid. An efficient forecasting model is proposed in this paper to predict the next-day solar photovoltaic power using the Levenberg-Marquardt (LM) and Bayesian Regularization (BR) algorithms and r...

In this paper, we present a primal-dual interior-point method for solving nonlinear programming problems. It employs a Levenberg-Marquardt (LM) perturbation to the Karush-Kuhn-Tucker (KKT) matrix to handle indefinite Hessians and a line search to obtain sufficient descent at each iteration. We show that the LM perturbation is equivalent to replacing the Newton step by a cubic regularization ste...

In this paper, a channel estimator based on an adaptive neuro fuzzy inference system (ANFIS) is proposed for the purpose of estimating channel frequency responses in orthogonal frequency division multiplexing-interleave division multiple access (OFDM-IDMA) systems. To see the performance of our proposed channel estimation method, five different techniques including well-known pilot-based estima...

In this paper, we consider a nonlinear least squares model for the phase retrieval problem. Since the Hessian matrix may not be positive definite and the Gauss-Newton (GN) matrix is singular at any optimal solution, we propose a modified Levenberg-Marquardt (LM) method, where the Hessian is substituted by a summation of the GN matrix and a regularization term. Similar to the well-known Wirtinge...

In a modern small gasoline engine fuel injection system, the load of the engine is estimated based on the measurement of the manifold absolute pressure (MAP) sensor, which took place in the intake manifold. This paper present a more economical approach on estimating the MAP by using only the measurements of the throttle position and engine speed, resulting in lower implementation cost. The esti...

This paper proposes a multi-scale parameter identification algorithm for the lithium-ion battery (LIB) electric model by using a combination of particle swarm optimization (PSO) and Levenberg-Marquardt (LM) algorithms. Two-dimensional Poisson equations with unknown parameters are used to describe the potential and current density distribution (PDD) of the positive and negative electrodes in the...