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- W2742230720 abstract "In this paper, we address multi-step ahead time series Prediction Intervals (PI). We extend two Neural Network (NN) methods, Lower Upper Bound Estimation (LUBE) and Multi-objective Evolutionary Algorithm (MOEA) LUBE (MLUBE), for multi-step PI. Furthermore, we propose two new MOEA methods based on a 2-phase gradient and MOEA based learning: M2LUBET1 and M2LUBET2. Also, we present a robust evaluation procedure to compare PI methods. Using four distinct seasonal time series, we compared all four PI methods. Overall, competitive results were achieved by the 2-phase learning methods, in terms of both predictive performance and computational effort." @default.
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- W2742230720 date "2017-01-01" @default.
- W2742230720 modified "2023-09-22" @default.
- W2742230720 title "Multi-objective Learning of Neural Network Time Series Prediction Intervals" @default.
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- W2742230720 doi "https://doi.org/10.1007/978-3-319-65340-2_46" @default.
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