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Wyszukujesz frazę "neural modelling" wg kryterium: Temat


Wyświetlanie 1-3 z 3
Tytuł:
Time-varying time-delay estimation for nonlinear systems using neural networks
Autorzy:
Tan, Y.
Powiązania:
https://bibliotekanauki.pl/articles/907277.pdf
Data publikacji:
2004
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
modelowanie procesu
opóźnienie czasowe
układ nieliniowy
sieć neuronowa
modelling
time delay
nonlinear systems
neural networks
estimation
Opis:
Nonlinear dynamic processes with time-varying time delays can often be encountered in industry. Time-delay estimation for nonlinear dynamic systems with time-varying time delays is an important issue for system identification. In order to estimate the dynamics of a process, a dynamic neural network with an external recurrent structure is applied in the modeling procedure. In the case where a delay is time varying, a useful way is to develop on-line time-delay estimation mechanisms to track the time-delay variation. In this paper, two schemes called direct and indirect time-delay estimators are proposed. The indirect time-delay estimator considers the procedure of time-delay estimation as a nonlinear programming problem. On the other hand, the direct time-delay estimation scheme applies a neural network to construct a time-delay estimator to track the time-varying time-delay. Finally, a numerical example is considered for testing the proposed methods.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2004, 14, 1; 63-68
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Development of cost estimation models based on ANN ensembles and the SVM method
Autorzy:
Juszczyk, Michał
Powiązania:
https://bibliotekanauki.pl/articles/396649.pdf
Data publikacji:
2020
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
construction cost estimation
cost modelling
ensemble of neural networks
support vector machine
koszty budowy
modelowanie kosztów
zespół sieci neuronowych
Opis:
Cost estimation, as one of the key processes in construction projects, provides the basis for a number of project-related decisions. This paper presents some results of studies on the application of artificial intelligence and machine learning in cost estimation. The research developed three original models based either on ensembles of neural networks or on support vector machines for the cost prediction of the floor structural frames of buildings. According to the criteria of general metrics (RMSE, MAPE), the three models demonstrate similar predictive performance. MAPE values computed for the training and testing of the three developed models range between 5% and 6%. The accuracy of cost predictions given by the three developed models is acceptable for the cost estimates of the floor structural frames of buildings in the early design stage of the construction project. Analysis of error distribution revealed a degree of superiority for the model based on support vector machines.
Źródło:
Civil and Environmental Engineering Reports; 2020, 30, 3; 48-67
2080-5187
2450-8594
Pojawia się w:
Civil and Environmental Engineering Reports
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Dynamic Neural Networks for Process Modelling in Fault Detection and Isolation Systems
Autorzy:
Korbicz, J.
Patan, K.
Obuchowicz, A.
Powiązania:
https://bibliotekanauki.pl/articles/908291.pdf
Data publikacji:
1999
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
wykrywanie błędu
sieć neuronowa dynamiczna
modelowanie nieliniowe
algorytm inteligentny
fault detection
dynamic neural networks
non-linear modelling
learning algorithms
FL-classifier
two-tank system
Opis:
A fault diagnosis scheme for unknown nonlinear dynamic systems with modules of residual generation and residual evaluation is considered. Main emphasis is placed upon designing a bank of neural networks with dynamic neurons that model a system diagnosed at normal and faulty operating points.To improve the quality of neural modelling, two optimization problems are included in the construction of such dynamic networks: searching for an optimal network architecture and the network training algorithm. To find a good solution, the effective well-known cascade-correlation algorithm is adapted here. The residuals generated by a bank of neural models are then evaluated by means of pattern classification. To illustrate the effectiveness of our approach, two applications are presented: a neural model of Narendra's system and a fault detection and identification system for the two-tank process.
Źródło:
International Journal of Applied Mathematics and Computer Science; 1999, 9, 3; 519-546
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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