ANN

Study and analysis of partial shading effect on power production of a photovoltaic string controlled by three different MPPT techniques: P&O, PSO and ANN

Partial shading occurs when some of the solar panels are exposed to reduced irradiation.  Partial shading can lead to creating peaks and troughs in power production.  The goal of this study is to compare the effect of partial shading on the capacity of maximum power point tracking (MPPT) methods, to find the global maximum power point.  To this end, the study focuses on performance simulation and discussion of Perturb and Observe (P&O), Particle Swarm Optimization (PSO), and Artificial Neural Network (ANN) controls.  Analysing the three MPPT controller's results, in

Data classification of spectrum analysis using neural network

This article provides the comparison of libraries neural networks. Based on this analysis was determined to develop a neural network for classification of spectra based on Encog library, because it implemented many components and gives the best result with a small number of items for training. Showed the architecture of neural networks for data classification of spectral analysis.

Verification of data for the implementation of the forecast of dollar using artificial neural networks

The moving average method with the 4 samples window width is used to raise the weekly forecast of the US dollar exchange rate accuracy. The non-iterative artificial neural network with the radial basis functions is used for. In the end we got the forecast error less than 1%

Integrated automated system for the implementation of forecast of consumption electrical energy in lviv region

The IAS "Forecast" is developed for forecasting the electricity consumption in the original production conditions at PJSC "Lvivoblenergo." The statistical and neural network methods are used for the input data verification; is enhanced the space dimensions extending methods for the incoming data to use them with the ANN with non-iterative training