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
doaj +4 more sources
The Symmetric Mean Absolute Percentage Error: Unnecessary or Dangerous
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
doaj +4 more sources
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
doaj +3 more sources
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
doaj +4 more sources
A Hybrid Neural Network Model for Short-Term Wind Speed Forecasting
Energies, 2023 This study proposes an effective wind speed forecasting model combining a data processing strategy, neural network predictor, and parameter optimization method.
Shengxiang Lv, Lin Wang, Sirui Wang
doaj +2 more sources
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
doaj +3 more sources
A Prediction Method of Seedling Transplanting Time with DCNN-LSTM Based on the Attention Mechanism
Agronomy, 2022 To improve the production efficiency and reduce the labor cost of seedling operations, cabbage was selected as the research subject, and a novel approach based on the attention mechanism combining the deep convolutional neural network (DCNN) and long ...
Huaji Zhu, Chang Liu, Huarui Wu
doaj +2 more sources
Short-Term Prediction of COVID-19 Using Novel Hybrid Ensemble Empirical Mode Decomposition and Error Trend Seasonal Model [PDF]
Frontiers in Public Health, 2022 In this article, a new hybrid time series model is proposed to predict COVID-19 daily confirmed cases and deaths. Due to the variations and complexity in the data, it is very difficult to predict its future trajectory using linear time series or ...
Dost Muhammad Khan +7 more
doaj +2 more sources
Systems Science & Control EngineeringThe dependence of wind power on the natural environment leads to volatility, which can cause hidden dangers to the safe and stable operation of the power grid.
Pingping Xie +5 more
doaj +2 more sources
Short-term load forecasting using a metaheuristic optimized temporal fusion transformer with decomposition technique [PDF]
Frontiers in Artificial IntelligenceShort-term load forecasting plays a vital role in today's modern life to ensure the balance between energy demand and supply. Dynamic variations in weather and electricity consumption patterns can significantly influence load patterns, resulting in ...
Radhika Chandrasekaran +1 more
doaj +2 more sources