Accurate and timely weather forecasting is a major challenge for the scientific community in hydrological research such as river training works and design of flood warning systems. Neural Network (NN) is a popular regression method in rainfall predictive modeling. This paper investigates the effectiveness of the hybrid Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) evolved neural ...

This paper presents the system identification and design of a neural network based Proportional, Integral and Derivative (PID) controller for a two degree of freedom (2DOF), quarter-car active suspension system. The controller design consists of a PID controller in a feedback loop and a neural network feedforward controller for the suspension travel to improve the vehicle ride comfort and handl...

This work addresses an autonomous underwater vehicle (AUV) for applying nonlinear control which is capable of disturbance rejection via intelligent estimation of uncertainties. Adaptive radial basis function neural network (RBF NN) controller is proposed to approximate unknown nonlinear dynamics. The problem of designing an adaptive RBF NN controller was augmented with sliding mode robust term ...

This paper investigates the application of wavelet transform as a preprocessor for neural networks (NN) in identifying internal turn-to-turn faults in transformer windings. The faulty and normal signals generated by numerical simulation of ElectroMagnetic Transient Program (EMTP) are preprocessed using discrete wavelet transform (DWT). The mean values of the wavelet coefficients are input into ...

In this paper, we propose an approach for detection of anomalies present in medical images. The idea is to combine tow metaphors: Neural Networks (NN) and Evolutionary Algorithm (EA) in a hybrid system. The Radial Basis Function Neural Network (RBF NN) and Multi Population Genetic Algorithm (MPGA) are coupled in one system called neural-evolutionary algorithm. After applying the growing region ...

This paper presents design and implementation of three new Infrared Counter-Countermeasure (IRCCM) efficient methods using Neural Network (NN), Fuzzy System (FS), and Kalman Filter (KF). The proposed algorithms estimate tracking error or correction signal when jamming occurs. An experimental test setup is designed and implemented for performance evaluation of the proposed methods. The methods v...

Neural Networks (NN) hold the potential for improving a variety of tasks in remote sensing and image processing. They represent a different approach to problems, as they do not rely on statistical relationships. Instead, neural networks adaptively estimate continuous functions from data without specifying mathematically how outputs depend on inputs. This paper evaluates the effect of metrics se...