- Tytuł:
- Identification Accuracy of Additional Wave Resistance Through a Comparison of Multiple Regression and Artificial Neural Network Methods
- Autorzy:
- Cepowski, T.
- Powiązania:
- https://bibliotekanauki.pl/articles/2065011.pdf
- Data publikacji:
- 2018
- Wydawca:
- STE GROUP
- Tematy:
-
identification
neural networks
regression
wave resistance - Opis:
- The article presents the use of multiple regression method to identify added wave resistance. Added wave resistance was expressed in the form of a four-state nominal function of: “thrust”, “zero”, “minor” and “major” resistance values. Three regression models were developed for this purpose: a regression model with linear variables, nonlinear variables and a large number of nonlinear variables. The nonlinear models were developed using the author's algorithm based on heuristic techniques. The three models were compared with a model based on an artificial neural network. This study shows that non-linear equations developed through a multiple linear regression method using the author’s algorithm are relatively accurate, and in some respects, are more effective than artificial neural networks.
- Źródło:
-
Multidisciplinary Aspects of Production Engineering; 2018, 1, 1; 197--204
2545-2827 - Pojawia się w:
- Multidisciplinary Aspects of Production Engineering
- Dostawca treści:
- Biblioteka Nauki
Artykuł