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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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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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
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Jurnal Profesi Insinyur Universitas LampungBanyaknya metode Machine learning dalam prediksi menyebabkan pemilihan algoritma menjadi penting karena setiap metode memiliki kemampuan berbeda dalam mengolah karakteristik data. Perbedaan performa antar metode menunjukkan perlunya pengujian untuk menentukan algoritma yang sesuai dalam menghasilkan prediksi akurat.
Neforinez Pedovanka +3 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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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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Vertical wind speed extrapolation using statistical approaches [PDF]
FME TransactionsThe wind power industry has experienced a significant increase and popularity in recent times, and the latest statistics indicate that this sector is still thriving.
Nuha Hilal H. +4 more
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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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