Temat: MLP - Prolib Integro

Skocz do pozycji: 1.

Tytuł:: Forecasting the Energy Consumption of an Industrial Enterprise Based on the Neural Network Model
Autorzy:: Kalinchyk, Vasyl
Meita, Olexandr
Pobigaylo, Vitalii
Kalinchyk, Vitalii
Filyanin, Danylo
Tematy:: electrical load
daily schedule
modelling
neural network
multilayer perceptron
MLP; Pokaż więcej
Wydawca:: Politechnika Koszalińska. Wydawnictwo Uczelniane
Powiązania:: https://bibliotekanauki.pl/articles/2069887.pdf Link otwiera się w nowym oknie
Opis:: This research paper investigates the application of neural network models for forecasting in energy. The results of forecasting the weekly energy consumption of the enterprise according to the model of a multilayer perceptron at different values of neurons and training algorithms are given. The estimation and comparative analysis of models depending on model parameters is made.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Neural Network Model for Control of Operating Modes of Crushing and Grinding Complex
Autorzy:: Kalinchyk, Vasyl
Meita, Olexandr
Pobigaylo, Vitalii
Borychenko, Olena
Kalinchyk, Vitalii
Tematy:: classification
modelling
neural network
radial basis function network
RBF
multilayer perceptron
MLP; Pokaż więcej
Wydawca:: Politechnika Koszalińska. Wydawnictwo Uczelniane
Powiązania:: https://bibliotekanauki.pl/articles/2174915.pdf Link otwiera się w nowym oknie
Opis:: This article investigates the application of neural network models to create automated control systems for industrial processes. We reviewed and analysed works on dispatch control and evaluation of equipment operating modes and the use of artificial neural networks to solve problems of this type. It is shown that the main requirements for identification models are the accuracy of estimation and ease of algorithm implementation. It is shown that artificial neural networks meet the requirements for accuracy of classification problems, ease of execution and speed. We considered the structures of neural networks that can be used to recognise the modes of operation of technological equipment. Application of the model and structure of networks with radial basis functions and multilayer perceptrons for identifying the mode of operation of equipment under given conditions is substantiated. The input conditions for constructing neural network models of two types with a given three-layer structure are offered. The results of training neural models on the model of a multilayer perceptron and a network with radial basis functions are presented. The estimation and comparative analysis of models depending on model parameters are made. It is shown that networks with radial basis functions offer greater accuracy in solving identification problems. The structural scheme of the automated process control system with mode identification based on artificial neural networks is offered.
Dostawca treści:: Biblioteka Nauki

Artykuł

na półce

Skocz do pozycji: 3.

Tytuł:: Development of a neural statistical model for the prediction of relative humidity levels in the region of Rabat-Kenitra, North West Morocco
Autorzy:: El Azhari, Kaoutar
Abdallaoui, Badreddine
Dehbi, Ali
Abdalloui, Abdelaziz
Zineddine, Hamid
Tematy:: artificial neural network
ANN
learning algorithm
multi-layer perceptron
MLP
modelling
Rabat-Kenitra
relative humidity; Pokaż więcej
Wydawca:: Instytut Technologiczno-Przyrodniczy
Powiązania:: https://bibliotekanauki.pl/articles/2174362.pdf Link otwiera się w nowym oknie
Opis:: This article accounts for the development of a powerful artificial neural network (ANN) model, designed for the prediction of relative humidity levels, using other meteorological parameters such as the maximum temperature, minimum temperature, precipitation, wind speed, and intensity of solar radiation in the Rabat-Kenitra region (a coastal area where relative humidity is a real concern). The model was applied to a database containing a daily history of five meteorological parameters collected by nine stations covering this region from 1979 to mid-2014. It has been demonstrated that the best performing three-layer (input, hidden, and output) ANN mathematical model for the prediction of relative humidity in this region is the multi-layer perceptron (MLP) model. This neural model using the Levenberg-Marquard algorithm, with an architecture of [5-11-1] and the transfer functions Tansig in the hidden layer and Purelin in the output layer, was able to estimate relative humidity values that were very close to those observed. This was affirmed by a low mean squared error (MSE) and a high correlation coefficient (R), compared to the statistical indicators relating to the other models developed as part of this study.
Dostawca treści:: Biblioteka Nauki

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