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Is average RMSE appropriate for evaluating acoustic-to-articulatory inversion?
2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2019Acoustic-to-articulatory inversion has potential application in number of fields. For decades, average root mean square error and Pearson correlation coefficient are the most prevalent quantities adopted to evaluate the performance of acoustic-to-articulatory inversion.
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RMSE POWER COEFFICIENT OF WIND TURBINES WITH INVERSE TOQUE-SPEED CONTROL
ShodhKosh: Journal of Visual and Performing ArtsThe Blade Element Momentum (BEM) method stands out among various turbine modelling techniques due to its integration of airfoil aerodynamics with momentum theory, allowing detailed force calculations on blade elements. While traditional methods like BEM and Wake Models are efficient for initial turbine design, advancements in computational power have ...
Rishikesh Choudhary +2 more
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An Optimized DTW Algorithm Using the RMSE Approach to Classify the Liquids in Ka-Band
IETE Journal of Research, 2020ABSTRACTIn this paper, a new optimized algorithm is presented to classify the liquids with high-level accuracy using raw data which show the transmission parameter (S21) of liquids.
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Clustering Analysis to Improve Web Search Ranking Using PCA and RMSE
2020Classification of web pages is the first step of web page ranking (or we can call it indexing), one of the most common ways to achieve indexing process is clustering that pages into groups as per the similarity, whenever the misclassification is less, the result will be perfect. Moreover, clustering is a collection of algorithms that dive the data into
Mohammed A. Ko’adan +2 more
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Fast Fractal Image Coding Method Based on RMSE and DCT Classification
Applied Mechanics and Materials, 2012To solve the problem of long time consuming in the fractal encoding process, a fast fractal encoding algorithm based on RMSE (Root mean square error) and DCT (Discrete Cosine Transform) classification is proposed. During the encoding process, firstly, the image is divided into range blocks and domain blocks by quadtree partition according to RMSE, then,
Xian Qiang Lv +5 more
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Estimating Fuzzy Membership Function Based on RMSE for the Positional Accuracy of Historical Maps
2007 International Workshop on the Analysis of Multi-temporal Remote Sensing Images, 2007When combining data from a time period spanning 300 years, these data will originate from various sources, and will be created by a diversity of techniques. Different spatial data types have different sources of error and provide information at varying accuracy levels.
Eva M. de Clercq, Robert R. de Wulf
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Friction estimation – optimization of sensor configuration with respect to RMSE and costs
2014The accuracy of friction estimation depends on the sensors used. Furthermore, the costs of sensors have to be considered during system design.
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Multi-Layered Cardiac Arrhythmia Detection Using RMSE Method
2023 IEEE International Conference on Contemporary Computing and Communications (InC4), 2023A Raja +3 more
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RMSE Reduction for GMM Estimators of Linear Time Series Models [PDF]
, 2000 In this paper we analyze GMM estimators for time series models as advocated by Hayashi and Sims, and Hansen and Singleton. It is well known that these estimators achieve efficiency bounds if the number of lagged observations in the instrument set goes to infinity. A new version of the GMM estimator based on kernel weighted moment conditions is proposed.
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Root-mean-square error (RMSE) or mean absolute error (MAE): when to use them or not
Geoscientific Model Development, 2022Timothy Hodson
exaly