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Unilateral boundary time series forecasting [PDF]

open access: yesFrontiers in Big Data
Time series forecasting is an essential tool across numerous domains, yet traditional models often falter when faced with unilateral boundary conditions, where data is systematically overestimated or underestimated. This paper introduces a novel approach
Chao-Min Chang, Cheng-Te Li, Shou-De Lin
doaj   +4 more sources

Woa-wtconv-kanformer for long term time series forecasting. [PDF]

open access: yesPLoS ONE
Multivariate time series analysis and prediction are of great significance in traffic management, weather forecasting and other practical applications.
Meng Ling Ming   +3 more
doaj   +3 more sources

Mamba time series forecasting with uncertainty quantification [PDF]

open access: yesMachine Learning: Science and Technology
State 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
doaj   +2 more sources

Cheng Fuzzy Time Series Model to Forecast the Price of Crude Oil in Malaysia

open access: yesJournal 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
doaj   +3 more sources

Time Series Smoothing Improving Forecasting

open access: yesApplied 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
doaj   +1 more source

Time Series Forecasting for Energy Consumption

open access: yesEnergies, 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
doaj   +1 more source

Compression-Based Methods of Time Series Forecasting

open access: yesMathematics, 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
doaj   +1 more source

Forecasting of GPU Prices Using Transformer Method

open access: yesJurnal 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
doaj   +1 more source

Financial time series forecasting methods [PDF]

open access: yesITM Web of Conferences
The paper presents the development of time series forecasting algorithms based on the Integrated Autoregressive Moving Average Model (ARIMA) and the Fourier Expansion model.
Zinenko Anna, Stupina Alena
doaj   +1 more source

A Time Series Forecasting Method

open access: yesITM Web of Conferences, 2017
This paper proposes a novel time series forecasting method based on a weighted self-constructing clustering technique. The weighted self-constructing clustering processes all the data patterns incrementally.
Wang Zhao-Yu   +3 more
doaj   +1 more source

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