Multilayered feed-forward neural networks trained with back-propagation algorithm are one of the most popular “online” artificial neural networks. These networks are showing strong inherit parallelism because of the influence of high number of simple computational elements. So it is natural to try to implement this kind of parallelism on parallel computer architecture. The Parallel Hybrid Ring ...

The optimum design of solar energy systems strongly depends on the accuracy of  solar radiation data. However, the availability of accurate solar radiation data is undermined by the high cost of measuring equipment or non-functional ones. This study developed a feed-forward backpropagation artificial neural network model for prediction of global solar radiation in Makurdi, Nigeria (7.7322  N lo...

This study focuses on the estimation of the mean grain size of mechanically induced Hydroxyapatite (HA) through the artificial neural network (ANN) model. The mean grain size of HA and HA based nanocomposites at different milling parameters were obtained from previous studies. The data were trained and tested by the neural network modeling. Accordingly, all data (55 sets) were based on the mecha...

In current scenario of software industries, Software effort estimation is very important task for software manager for successful completion of the project. Prediction is always challenging task and in recent days effort estimation take many researcher’s attention. Prediction with more accuracy is also an important for prediction models. We use Feed-Forward Neural Network for software developme...

This paper, presents a theoretical and practical basis of preprocessing on handwritten text for character recognition using forward-feed neural networks. Afterwards, the Feed forward algorithm gives working of a neural network followed by the Back Propagation Algorithm which compromises Training, Calculating Error, and Modifying Weights. The proposed solutions focus on applying Back Propagation...

In this paper we developed a spiking neural network model that learns to generate online handwriting movements. The architecture is a feed forward network with one hidden layer. The input layer uses a set of Beta elliptic parameters. The hidden layer contains both excitatory and inhibitory neurons. Whereas the output layer provides the script coordinates x(t) and y(t). The proposed spiking neur...

this article addresses an efficient and novel method for singularity-free path planning and obstacle avoidance of parallel manipulator based on neural networks. a modified 4-5-6-7 interpolating polynomial is used to plan a trajectory for a spherical parallel manipulator. the polynomial function which is smooth and continuous in displacement, velocity, acceleration and jerk is used to find a pat...

Developing artificial neural network (ANN), a model to make a correct prediction of required force and torque in ring rolling process is developed for the first time. Moreover, an optimal state of process for specific range of input parameters is obtained using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) methods. Radii of main roll and mandrel, rotational speed of main roll, pr...

This paper employs the continuous-time analogue Hopfield neural network to compute the temperature distribution in forward heat conduction problems and solves inverse heat conduction problems by using a back propagation neural (BPN) network to identify the unknown boundary conditions. The weak generalization capacity of BPN networks is improved by employing the Bayesian regularization algorithm...

In this paper we address the problem of rejecting Out-Of-Vocabulary words in speaker-independent Mandarin place name recognition. We integrate neural network and Hidden Markov Models in an attempt to utilize the strength of both. HMM based acoustic models including keyword models, filler models, and an anti-keyword model were trained to meet our needs. Statistical features are fed to a neural n...