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- W2896087287 abstract "Abstract 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." @default.
- W2896087287 created "2018-10-26" @default.
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- W2896087287 date "2018-09-01" @default.
- W2896087287 modified "2023-10-14" @default.
- W2896087287 title "Identification Accuracy of Additional Wave Resistance Through a Comparison of Multiple Regression and Artificial Neural Network Methods" @default.
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- W2896087287 doi "https://doi.org/10.2478/mape-2018-0026" @default.
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