Root mean square error (RMSE) or mean absolute error (MAE)? [PDF]
Geoscientific Model Development, 2014 Abstract. Both the root mean square error (RMSE) and the mean absolute error (MAE) are regularly employed in model evaluation studies. Willmott and Matsuura (2005) have suggested that the RMSE is not a good indicator of average model performance and might be a misleading indicator of average error and thus the MAE would be a better metric for that ...
T. Chai, R. R. Draxler
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Improved terrain estimation from spaceborne lidar in tropical peatlands using spatial filtering
Science of Remote Sensing, 2023 Tropical peatlands are estimated to hold carbon stocks of 70 Pg C or more as partly decomposed organic matter, or peat. Peat may accumulate over thousands of years into gently mounded deposits called peat domes with a relief of several meters over ...
Alexander R. Cobb +6 more
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Forecasting Wind Energy Production Using Machine Learning Techniques [PDF]
E3S Web of Conferences, 2023 Wind energy is an essential source of renewable energy that has gained popularity in recent years. Accurately forecasting wind energy production is crucial for efficient energy management and distribution.
Margarat G. Simi +3 more
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A symptotic Bias for GMM and GEL Estimators with Estimated Nuisance Parameter [PDF]
, 2003 This papers studies and compares the asymptotic bias of GMM and generalized empirical likelihood (GEL) estimators in the presence of estimated nuisance parameters.
Newey, Whitney K. +2 more
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Geometric View of Measurement Errors [PDF]
, 2010 The slope of the best fit line from minimizing the sum of the squared oblique errors is the root of a polynomial of degree four. This geometric view of measurement errors is used to give insight into the performance of various slope estimators for the ...
Copas J. +10 more
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A Comparison of Root Mean Square Errors on Skeletonization Methods [PDF]
International Journal of Applied Physics and Mathematics, 2012 Vectorization is the most fundamental operation in interpretation of line drawings and document analysis. There are several reasons for converting image vectorization. Vector data is normally created from existing natural source image like photographs, scanned images.
Neeti Daryal, Vinod Kumar
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Modelling the spatial distribution of DEM Error [PDF]
, 2005 Assessment of a DEM’s quality is usually undertaken by deriving a measure of DEM accuracy – how close the DEM’s elevation values are to the true elevation.
Bolstad P V +23 more
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Investigation of the efficiency of support vector machine in predicting changes in water quality parameters (Case study: Choghakhor International Wetland) [PDF]
بومشناسی آبزیان, 2020 Inland waters, such as wetlands, are considered to be sensitive ecosystems, and sustainable productivity can only be achieved by adopting an appropriate environmental approach.
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Multi-region electricity demand prediction with ensemble deep neural networks.
PLoS ONE, 2023 Electricity consumption prediction plays a vital role in intelligent energy management systems, and it is essential for electricity power supply companies to have accurate short and long-term energy predictions.
Muhammad Irfan +9 more
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Use of Machine Learning to Predict the Glycemic Status of Patients with Diabetes
Medical Sciences Forum, 2022 In this work, a machine learning methodology is used to predict the progress of the glycemic values of six patients with diabetes. Eight different algorithms are compared i.e., ANN, PNN, Polynomial Regression, Gradient Boosted Trees Regression, Random ...
Alessandro Massaro +4 more
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