Optimum design of chamfer masks using symmetric mean absolute percentage error [PDF]
EURASIP Journal on Image and Video Processing, 2019 Distance transform, a central operation in image and video analysis, involves finding the shortest path between feature and non-feature entries of a binary image.
Baraka Jacob Maiseli
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A new accuracy measure based on bounded relative error for time series forecasting. [PDF]
PLoS ONE, 2017 Many accuracy measures have been proposed in the past for time series forecasting comparisons. However, many of these measures suffer from one or more issues such as poor resistance to outliers and scale dependence.
Chao Chen +2 more
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Using Multivariate Adaptive Regression Splines to Estimate Summed Stress Score on Myocardial Perfusion Scintigraphy in Chinese Women with Type 2 Diabetes: A Comparative Study with Multiple Linear Regression [PDF]
DiagnosticsBackground: Myocardial perfusion scintigraphy (MPS) is an important tool for evaluating ischemia in diabetic populations. However, applications of advanced predictive models like multivariate adaptive regression splines (MARS) to estimate summed stress ...
Chien-Han Yuan +5 more
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The Symmetric Mean Absolute Percentage Error: Unnecessary or Dangerous [PDF]
ForecastingThe symmetric Mean Absolute Percentage Error (sMAPE) is a forecast error metric that has been proposed as an alternative to the more common Mean Absolute Percentage Error (MAPE), which is undefined whenever an actual is zero; the sMAPE does not have this
Stephan Kolassa
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Forecasting multidrug-resistant organisms infection trends in a Chinese tertiary hospital (2014–2024): a comparative study of SARIMA, ETS, Prophet, and NNETAR models [PDF]
Frontiers in Public HealthBackgroundInfections caused by multidrug-resistant organisms (MDROs) continue to pose serious challenges for hospital infection control, often resulting in longer hospitalizations, increased patient morbidity, and higher healthcare costs.
Haiyan Chen, Luojing Zhou
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Forecasting Tuberculosis Incidence in Somalia: A Comparative Analysis of Single and Hybrid Time‐Series Models [PDF]
Health Science ReportsBackground Tuberculosis (TB) remains a significant public health challenge, necessitating accurate forecasting methodologies to support effective control and prevention strategies. This paper explores the application and comparative performance of single
Hana Mahdi Dahir +4 more
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ChatGPT's performance in sample size estimation: a preliminary study on the capabilities of artificial intelligence. [PDF]
Fam PractBackground Artificial intelligence tools, including large language models such as ChatGPT, are increasingly integrated into clinical and primary care research.
Sebo P, Wang T.
europepmc +2 more sources
Macroeconomic-aware forecasting of construction costs in developing countries: Using gated recurrent unit and long short-term memory deep learning framework. [PDF]
PLoS ONECost overruns are common on long-term construction projects. This is mostly because of inaccurate early estimates and unexpected changes in the economy and finances.
Majed Alzara +5 more
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IEEE AccessDiscrepancies in custody transfer systems in the oil and gas industry pose significant financial, regulatory, and operational risks. Accurate prediction of these discrepancies is critical to optimizing operations and minimizing potential losses.
Fiki Hidayat +4 more
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IEEE AccessWind is unstable and unpredictable, and power generation is not constant. Wind speed prediction reduces these disadvantages, and it is essential to measure accurate wind speed predictions to install and stabilize wind power generation systems.
J. Sathyaraj, V. Sankardoss
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