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Woa-wtconv-kanformer for long term time series forecasting [PDF]
PLoS ONEMultivariate time series analysis and prediction are of great significance in traffic management, weather forecasting and other practical applications.
Meng Ling Ming +3 more
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Mamba time series forecasting with uncertainty quantification [PDF]
Machine Learning: Science and TechnologyState space models, such as Mamba, have recently garnered attention in time series forecasting (TSF) due to their ability to capture sequence patterns. However, in electricity consumption benchmarks, Mamba forecasts exhibit a mean error of approximately ...
Pedro Pessoa +4 more
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Cheng Fuzzy Time Series Model to Forecast the Price of Crude Oil in Malaysia
Journal of Computing Research and Innovation, 2022 Crude oil is one of the important commodities to Malaysia. As a producer and exporter of oil and gas, Malaysia has gained high Gross Revenue from this sector. Crude oil is the global commodity and highly demanded.
Jasmani Bidin +4 more
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Time Series Smoothing Improving Forecasting
Applied Computer Systems, 2021 Both statistical and neural network methods may fail in forecasting time series even operating on a great amount of data. It is an open question of which amount fits best to make sufficiently accurate forecasts on it. This implies that the length or time
Romanuke Vadim
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Forecasting with time series imaging [PDF]
Expert Systems with Applications, 2020 Feature-based time series representations have attracted substantial attention in a wide range of time series analysis methods. Recently, the use of time series features for forecast model averaging has been an emerging research focus in the forecasting community.
Xixi Li, Yanfei Kang, Feng Li 0028
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A Framework for Imbalanced Time-Series Forecasting [PDF]
, 2022 Time-series forecasting plays an important role in many domains. Boosted by the advances in Deep Learning algorithms, it has for instance been used to predict wind power for eolic energy production, stock market fluctuations, or motor overheating. In some of these tasks, we are interested in predicting accurately some particular moments which often are
Luis P. Silvestrin +2 more
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Compression-Based Methods of Time Series Forecasting
Mathematics, 2021 Time series forecasting is an important research topic with many practical applications. As shown earlier, the problems of lossless data compression and prediction are very similar mathematically.
Konstantin Chirikhin, Boris Ryabko
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Time Series Forecasting for Energy Consumption
Energies, 2022 Introduction In the last few years, there has been considerable progress in time series forecasting algorithms, which are becoming more and more accurate, and their applications are numerous and varied [...]
M. C. Pegalajar, L. G. B. Ruiz
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Nyström Regularization for Time Series Forecasting
CoRR, 2021 This paper focuses on learning rate analysis of Nyström regularization with sequential sub-sampling for $τ$-mixing time series. Using a recently developed Banach-valued Bernstein inequality for $τ$-mixing sequences and an integral operator approach based on second-order decomposition, we succeed in deriving almost optimal learning rates of Nyström ...
Zirui Sun +3 more
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Forecasting of GPU Prices Using Transformer Method
Jurnal Sisfokom, 2023 GPU or VGA (graphic processing unit) is a vital component of computers and laptops, used for tasks such as rendering videos, creating game environments, and compiling large amounts of code.
Risyad Faisal Hadi +2 more
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