Wyniki wyszukiwania - BazTech

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Calibration of reference torque transducer in one direction and use of its cubic coefficients in both directions with improved interpolation error

Khaled K. M., Osman Seif M.

Metrology and Measurement Systems

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2022

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Vol. 29, nr 3

539--551

EN

The current research work presents an investigation into use of the fitting coefficients resulting from the cubic curve fitting of the torque transducer calibration results in one direction to calculate the actual torque in the other torque direction with two methods: one is direct substitution with the nominal torque which gives a propagated linear relative interpolation error and the other is changing the sign of the second coefficient in the cubic function when using in the other torque direction. This proposed modification improves the absolute relative interpolation error by 5 to 16 times in the clockwise and counterclockwise directions based on the torque transducer’s classification.

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Curve fitting problem: torque–velocity relationship with polynomials and Boltzmann sigmoid functions

Milanov P., Koroleova G., Mavrevski R., Pencheva N.

Acta of Bioengineering and Biomechanics

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2018

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Vol. 20, no. 1

169--184

EN

The aim of this study was to investigate the curve fitting and model selection problem of the torque–velocity relationship of elbow flexors and extensors in untrained females. The second goal was to determine the optimal models in different function classes and the best, among the optimal ones. Lastly, test the best models to predict the torque were tested. Methods: Using the polynomials (second – fourth degree) and Boltzmann sigmoid functions, and a different presentation of data points (averages, a point cloud, etc.), we determined the optimal models by both error criteria: minimum residual sum of squares and minimum of the maximal absolute residue. To assess the best models, we applied Akaike and Bayesian information criteria, Hausdorff distance and the minimum of the smallest maximal absolute residue and the predictive torque–velocity relationships of the best models with torque values, calculated beyond the experimental velocity interval. Results: The application of different error and model selection criteria showed that the best models in the majority of cases were polynomials of fourth degree, with some exceptions from second and third degree. The criteria values for the optimal Boltzmann sigmoids were very close to those of the best polynomial models. However, the predicted torque–velocity relationships had physiological behavior only in Boltzmann’s sigmoid functions, and their parameters had a clear interpretation. Conclusion: The results obtained suggest that the Boltzmann sigmoid functions are suitable for modeling and predicting of the torque–velocity relationship of elbow flexors and extensors in untrained females, as compared to polynomials, and their curves are physiologically relevant.

3

Algorytmy genetyczne : Budowa wielomianowej funkcji modelu regresyjnego za pomocą algorytmu genetycznego i analiza statystyczna otrzymanych wyników w zależności od kształtu funkcji oceny

Wojnarowski K.

Studia i Materiały / Europejska Uczelnia Informatyczno-Ekonomiczna w Warszawie

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2014

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Nr 1(7)

49--63

PL

Celem pracy jest analiza algorytmu genetycznego dopasowującego wielomian do danych pomiarowych. W pierwszej części opisany jest użyty algorytm genetyczny oraz jego budowa. Druga część stanowi opis eksperymentu wykonanego przy użyciu opisywanego algorytmu i jakościowa analiza wyników. Dokonana została równie analiza statystyczna wyników otrzymanych dla różnych zestawów danych i różnych funkcji oceny algorytmu. Wysunięte wnioski podsumowują osiągnięte w eksperymencie wyniki oraz wyznaczają możliwy kierunek dalszych badań, mających na celu rozszerzenie zastosowań opisywanego algorytmu i poprawę jakości otrzymywanych rezultatów.

EN

The aim of this study is the analysis of a genetic algorithm fitting experiment data with polynomial. The first part consists of a description of algorithm used and its construction. The second part involves a description of an experiment performed using the described algorithm and qualitative analysis of the results. Additionally, there was performed a statistic analysis of the results – for different data sets and different fitting functions. Statements concluded, basing on the experiment, summarize its results and allow to point out goals for further research on the matter of creating regressive models using genetic algorithms and improving the quality of the results.