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 20 of 78 for “"Root Mean Squared Error"”.
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Design and fabrication of force sensing robotic foot utilizing the volumetric displacement of a hyperelastic polymer
… normal forces in the Z-axis up to 80 N with a root mean squared error of 6% but little information about shear forces in the X an Y-axis. The second iteration demonstrates an ability to pick up the presence and direction of shear forces up to 40 N but with a root mean squared error of 70%. This …
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Effect of upper stem diameter and errors of measurement on the accuracy of volume equations
… bias ranged from 0.85% for DBH measurement errors to 2.88% for total height measurement errors. Relative standard deviation ranged from 1.52% to 10.13% for DBH and total height errors respectively. When both bias and precision ( standard deviation ) were considered jointly, the relative root …
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Zjednodušování polygonálních sítí a optimalizace vykreslování pomocí technik Level of Detail
… Clustering, Floating Cell Clustering a Quadric Error Metrics. Tyto metody jsou následně porovnány pomocí metrik Hausdorffovy vzdálenosti a RMSE (Root Mean Squared Error). Výsledky prokazují, že nejvyšší geometrickou věrnost původnímu modelu zachovává zjednodušení dle metriky Quadric Error …
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Optimizing Local Least Squares Regression for Short Term Wind Prediction
… space which create a model with the lowest root mean squared error.
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Double Alternating Minimization (DAM) for Phase Retrieval in the Presence of Poisson Noise and Pixelation
… an accurate effective pupil function, where the squared modulus of its Fourier transform is detected by a camera. However, current algorithms such as the Gerchberg-Saxton algorithm and Fienup-style algorithm do not consider the detector sampling rate and shot noise introduced by photon detection. …
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Robustness of the achievable benchmark of care method
… of the standard ABC method, which uses the mean to calculate the benchmark, to versions of the ABC method where the mean was replaced with either a 5%, 10%, or 20% trimmed mean, a 15% Winsorized mean or the one-step Huber ø1.28 calculation. Monte Carlo simulations where conducted using …
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Three dimensional moving pictures with a single imager and microfluidic lens
… material, the depth is found to be an average Root Mean Squared Error (RMSE) of 3.543 gray level steps (1.38\%) accuracy compared to ranging data. The depth is inferred using a new Extended Depth from Defocus (EDfD), and defocus is achieved at movie speeds with a microfluidic lens. Camera …
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Indoor 3D Modeling Using Consumer Drones and Neural Simultaneous Localization and Mapping (SLAM) for Virtual Reality
… maintaining trajectory accuracy with 6.61 cm root mean squared error (RMSE) on the Replica benchmark. The modular architecture supports both web-based visualization and virtual reality through Oculus Quest 3, using WebSocket protocols for low- latency data streaming. Experimental evaluations …
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A comparison of some methods of modeling baseline hazard function in discrete survival models
… in smoothing the baseline hazard function. Root mean squared error (RMSE) analysis suggests that generally all the smoothing methods performed better than the model with a discrete baseline hazard function. No single smoothing method outperformed the other smoothing methods. These methods …
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A GAN-Augmented Machine Learning Framework for Predicting Raman Characteristics in Carbon Nanofiber Synthesis
… The augmented model achieved 𝑅2 ≃ 0.91, and root mean squared error of 0.065 for 𝐼𝐷 /𝐼𝐺 , outperforming unaugmented baselines (XGBoost 𝑅2 ≃ 0.76; support vector regression 𝑅2 ≃ 0.71). CTGAN preserved data characteristics (≃ 96–97 % marginal fidelity / relationship), allowing robust …
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Variations in Control and Display Gain in a First Control Order Compensatory Manual Tracking Task
… Tracking performance will be measured by the root mean squared error (RMSE) of tracking deviation as measured by the amount of distance that the element being controlled by participants under study deviated from the tracking device within a given time period.</p>
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Composite force sensing foot utilizing volumetric displacement of a hyperelastic polymer
… normal forces in the Z-axis up to 80N with a root mean squared error of 6.04% as well as the onset of shear in the X and Y-axis. This demonstrates a proof-of-concept for a more robust footpad sensor suitable for use in all outdoor conditions.
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Suspension Controls and Parameter Estimation Using Accelerometer Based Intelligent Tires
… were fed to a trained bagged trees model. Root mean squared error of 11% was observed on the test dataset. For velocity estimation, the data collected by the accelerometer was fed to a variational mode decomposition process. The extracted mode was converted to time-frequency domain using …
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A Comparison of Corn Yield Forecasting Models
… of adjusted R2 values, F-test values, and root Mean Squared Error (MSE) values are conducted, as well as statistical tests of the competing model forecast errors. The results show that the competing subjective (CCI) model performs the best at forecasting corn yield during the growing …
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A Comparison of Corn Yield Forecasting Models
… of adjusted R2 values, F-test values, and root Mean Squared Error (MSE) values are conducted, as well as statistical tests of the competing model forecast errors. The results show that the competing subjective (CCI) model performs the best at forecasting corn yield during the growing …
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A pseudo-Bayesian model-based approach for noninvasive intracranial pressure estimation
… plausible ICP values, and the resulting residual errors are transformed into likelihoods for each candidate ICP. The likelihoods are combined with a imulti-modal prior distribution of the ICP to yield an a posteriori distribution whose mode is taken as the final ICP estimate. An extension to this …
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An empirical comparison of autoregressive and rational models of price expectations
… extrapolations were generated and compared by means of the root-mean-squared error and Theil inequality coefficient. The outcome of these various tests provides support to the contention that, for an individual attempting to obtain optimal (error minimizing) forecasts of future inflation would …
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Essays in Global Commodity Prices and Realised Volatility
… of commodity prices (S&PGSCI) by comparing their Root Mean Squared Error (RMSE) to that from the usual benchmark AR (1). The Mixed Data Sampling models (MIDAS) allow us to obtain forecasts by keeping variables at their original frequencies and therefore to explore the richness of high frequency …
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Predictability of the Dollar- Rand exchange rate using Taylor Rule fundamentals and commodity Prices.
… Taylor rule specification, a Johansen Vector Error Correction Model (VECM) and a Random walk approach. The results from the Root Mean Squared Error (RMSE) show that the Random walk model outperforms both the Taylor rule and VECM models. This brings us to the conclusion that although commodity …
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Optimal Clustering: Genetic Constrained K-Means and Linear Programming Algorithms
… this dissertation, we propose two constrained k-means algorithms: Linear Programming Algorithm (LPA) and Genetic Constrained K-means Algorithm (GCKA). Linear Programming Algorithm modifies the k-means algorithm into a linear programming problem with constraints requiring that each cluster have m …
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