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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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
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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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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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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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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
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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
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A Large-Scale Wireless Cell Long-Term Daily-Granularity Forecasting Method
IEEE Access, 2022 Optimizing and managing wireless communication network, including improving the utilization of network resources, energy efficiency, automatically carrying out wireless network planning and network construction, is very important to the communication ...
Wei Fang, Yun Chen, Ning Pan, Bin Ran
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