An iteration optimization approach integrating backpropagation neural network (BPNN) with genetic algorithm (GA) is proposed. The main idea of the approach is that a BPNN model is first developed and trained using fewer learning samples, then the trained BPNN model is solved using GA in the feasible region to search the model optimum. The result of verification conducted based on this optimum i...

This work approaches the problem of estimating Kautz optimal poles in kernel expansion Wiener-Volterra models. The analytical solution for suboptimal case is already established literature. However, two parameters that compose still open. In this paper, an optimization strategy using Levenberg-Marquardt presented. algorithm used to find parameters, with same base all dimensions. construction ba...

*This research was carried out as part of NWO research project 611-304-019, 'Address: Free University, Department of Economics and Econometrics, De Boelelaan 1105, 1081 HV Amsterdam, The Netherlands. E-mail: [email protected].

In this paper, a Levenberg-Marquardt inspired sliding mode control theory based adaptation laws are proposed to train an intelligent fuzzy neural network controller for a quadrotor aircraft. The proposed controller is used to control and stabilize a quadrotor unmanned aerial vehicle in the presence of periodic wind gust. A proportional-derivative controller is firstly introduced based on which ...

Introduction: Energy resolving X-ray photon counting detectors are able to assign each detected photon to energy bins [1] (Figure 1). This allows the decomposition of an X-ray image into the materials of the acquired object [1, 2], which has potential benefits in angiography. Contrast agent can be extracted without acquiring a mask image, possibly saving dose and avoiding problems with patient ...

Singularities and uncertainty in manipulator dynamic is a major issue in kinematic control of manipulator which is obtained by applying robot model. In this paper, artificial neural networks with optimal training process and training data have been proposed as a way to solve this problem. The main idea of this approach is to use an artificial neural network to learn the characteristics of the r...

In the last decades, helicopter-borne electromagnetic (HEM) method became a focus of interest in the fields of mineral exploration, geological mapping, groundwater resource investigation and environmental monitoring. As a standard approach, researchers use 1-D inversion of the acquired HEM data to recover the conductivity/resistivity-depth models. Since the relation between HEM data and model ...

Artificial neural networks are applied to model the manoeuvrability characteristics of a ship based on empirical information acquired from experiments with scaled model. This work aims evaluate performance proposed method training artificial network even very small quantity noisy data. The data used for consisted zig-zag and circle manoeuvres carried out in agreement IMO standards. wind effect ...