A model of wavelet neural network (WNN) using a new evolutionary learning algorithm is proposed in this paper. This new evolutionary learning algorithm is based on a hybrid of Particle Swarm Optimization (PSO) and gradient descent algorithm (GD), and is thus called HGDPSO. The Particle Swarm Optimizer has previously been used to train neural networks and generally met with success. The advantag...

Abstract Rainfall–runoff modelling is crucial for enhancing the effectiveness and sustainability of water resources. Conceptual models can have difficulties, such as coping with nonlinearity needing more data, whereas data-driven be deprived reflecting physical process basin. In this regard, two hybrid model approaches, namely Génie Rural à 4 paramètres Journalier (GR4 J)–wavelet-based (i.e., w...

We present a forecasting strategy based on stationary wavelet transform combined with radial basis function (RBF) neural network to improve the accuracy of 3-month-ahead hake catches forecasting of the fisheries industry in the central southern Chile. The general idea of the proposed forecasting model is to decompose the raw data set into an annual cycle component and an inter-annual component ...

This contribution addresses forward kinematic solution of modular hybrid manipulator which includes two same Stewart mechanism in serial form known as 2-(6UPS) manipulator. First, using geometrical and vectorial analysis, mathematical model of kinematic analysis for 2-(6UPS) is extracted. As mapping the length of pods to location (orientation and position) of moving mid and upper platforms (for...

artificial neural networks (anns) are flexible computing frameworks and universal approximators that can be applied to a wide range of time series forecasting problems with a high degree of accuracy. however, despite of all advantages cited for artificial neural networks, they have data limitation and need to the large amount of historical data in order to yield accurate results. therefore, the...

Explosive ordnance disposal robot path planning is a nondeterministic polynomial time (NP) problem, traditional optimization methods are not very effective to it, which are easy to plunge into local minimum. In this paper, a new algorithm-Danger Model Immune Wavelet Neural Network (DIWNN) is improved. It is proposed to initialize the weights and biases of wavelet neural network (WNN), the ergod...

today, stock investment has become an important mean of national finance. apparently, it is significant for investors to estimate the stock price and select the trading chance accurately in advance, which will bring high return to stockholders. in the past, long-term trading processes and many technical analysis methods for stock market were put forward. however, stock market is a nonlinear sys...

This paper presents a new path-tracking scheme for a car-like mobile robot based on neural predictive control. A multi-layer back-propagation neural network is employed to model non-linear kinematics of the robot instead of a linear regression estimator in order to adapt the robot to a large operating range. The neural predictive control for path tracking is a model-based predictive control bas...