Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 11 of 11 for “"Root mean squared errors"”.
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Accuracy Improvement in Robotic Milling Through Data-Driven Modelling and Control
… and damping coefficient in its workspace with root mean squared errors of 3.31 Hz, 150 KN/m, and 810 Ns/m, respectively. The predicted modal parameters are used to predict the average peak-to-valley vibrations of the tool tip during robotic milling. The results show that the average …
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Futures-Based Forecasts of U.S. Crop Prices
… research evaluated model performance using R-squared, mean errors, root mean squared errors, the modified Diebold-Mariano test, and the encompassing test. The results show that both the difference model and the regime model render better performance than the benchmark in most cases, but …
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Statistically modelling tennis racket impacts with six degrees of freedom
… method was improved to correct for perspective errors associated with the proximity of the cameras to the test volume. The automated algorithms were validated with experimental data and manual methods. Multi-variate polynomial models to predict the lateral and vertical components of rebound …
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Impacts of Ignoring Nested Data Structure in Rasch/IRT Model and Comparison of Different Estimation Methods
… both 2-level and 3-level analysis. As for the root mean squared errors (RMSE), three methods performed without substantive differences for item difficulty estimates and ability variance estimates in both 2-level and 3-level analysis, except for level-2 ability variance estimates in 3-level …
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Three essays in financial economics
… tests, I find significant reductions in the root-mean-squared-errors upon incorporation of cost stickiness for all models. These findings suggest that professional macro forecasters do not fully incorporate the information contained in cost stickiness. In the second project, I investigate the …
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A Comparison of Bayesian Estimation Techniques in a Multidimensional Two-Parameter Partial Credit Item Response Model
… (low = .2, medium = .5, and high = .8). Root Mean Squared Errors (RMSE) and Bias for each of the recovered parameter in all the conditions were calculated. Sets of four-way ANOVAs were conducted to check the contribution of the four factors--Bayesian algorithm, prior choice, test length, …
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Modeling Nitrogen and Energy Metabolism in the Bovine
… assess the model accuracy and precision based on root mean squared errors (RMSE) and concordance correlation coefficients (CCC). Only slight mean and slope bias were exhibited for ruminal outflow of NDF, starch, lipid, total N, and non-ammonia N, and for fecal output of protein, NDF, lipid, and …
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Time Diversity Modelling and Implementation for Broadcast Satellite Systems at V-band
… models. The performance measure provided average root mean squared errors of 13%, 36% and 35% respectively. Also, comparison of the TD model with the actual measurements yielded a performance measure of <5% for link frequencies 20, 40 and 50 GHz.Statistical performance of a designed V-band (50/40 …
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Sampling scale sensitivities in surface ocean pCO2 reconstructions in the Southern Ocean
… (ML) and contributed to the convergence of the root mean squared errors (RMSEs) of ML methods to a common limit known in the literature as the “wall”. The hypothesis here is that addressing the critical missing sampling scale will get the community reconstructions of pCO2 “over the wall”. In …
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Nutritional and genetic characterization of dairy cows managed on pasture-based systems, identifying key aspects to improve their performance
… assess the model accuracy and precision based on root mean squared errors and concordance correlation coefficients (CCC). Predictions of protein and fiber digestion and fiber and organic matter fecal excretion were improved after model reparameterization, while body weight and body condition score …
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Improving Health and Safety at Surface and Underground Mines by Implementing Emerging Technologies Coupled With Geotechnical and Climatic Modeling
… trends following of the collected data. The root-mean squared errors (RMSE=√MSE) for Shafts #1-3 were 0.57 °C, 0.33 °C and 0.61 °C, respectively. These errors are low and are good predictions of the actual underground environment. Without the accurate prediction using NARXNN it has been shown …