Results 11 to 20 of about 517,907 (286)
Forecasting with time series imaging [PDF]
, 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 ...
Kang, Yanfei, Li, Feng, Li, Xixi
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Dense Sampling of Time Series for Forecasting
IEEE Access, 2022 A time series contain a large amount of information suitable for forecasting. Classical statistical and recent deep learning models have been widely used in a variety of forecasting applications.
Il-Seok Oh, Jin-Seon Lee
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TIME SERIES FORECASTING BY THE ARIMA METHOD
Scientific Journal of Astana IT University, 2022 The variety of communication services and the growing number of different sensors with the appearance of IoT (Internet of Things) technology generate significantly different types of network traffic.
Gulnara Bektemyssova +3 more
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Intuitionistic fuzzy time series functions approach for time series forecasting [PDF]
Granular Computing, 2020 AbstractFuzzy inference systems have been commonly used for time series forecasting in the literature. Adaptive network fuzzy inference system, fuzzy time series approaches and fuzzy regression functions approaches are popular among fuzzy inference systems.
Egrioglu, Erol, Bas, Eren, Yolcu, Ufuk
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Fuzzy Supervised Multi-Period Time Series Forecasting
Cybernetics and Information Technologies, 2019 The goal of this paper is to propose a new method for fuzzy forecasting of time series with supervised learning and k-order fuzzy relationships. In the training phase based on k previous historical periods, a multidimensional matrix of fuzzy dependencies
Ilieva Galina
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Forecasting Time Series with Boot.EXPOS Procedure
Revstat Statistical Journal, 2009 To forecast future values of a time series is one of the main goals in times series analysis. Many forecasting methods have been developed and its performance evaluated.
Clara Cordeiro , M. Manuela Neves
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Forecasting Method for Grouped Time Series with the Use of k-Means Algorithm
, 2015 The paper is focused on the forecasting method for time series groups with the use of algorithms for cluster analysis. $K$-means algorithm is suggested to be a basic one for clustering.
Astakhova, N. N. +2 more
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Multivariate dynamic kernels for financial time series forecasting [PDF]
, 2016 The final publication is available at http://link.springer.com/chapter/10.1007/978-3-319-44781-0_40We propose a forecasting procedure based on multivariate dynamic kernels, with the capability of integrating information measured at different frequencies ...
AJ Smola +6 more
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Forecasting Randomly Distributed Zero-Inflated Time Series
Folia Oeconomica Stetinensia, 2017 The main aim of the article is to propose a forecasting procedure that could be useful in the case of randomly distributed zero-inflated time series.
Doszyń Mariusz
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Recoletos Multidisciplinary Research Journal, 2020 Forecasting plays a critical part in implementing effective tourism management strategies. However, the role of tourism forecasting is not extensively studied in the Philippines, which is a key tourism destination in Southeast Asia.
Severina P. Velos +3 more
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