Results 11 to 20 of about 522,783 (291)
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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Probabilistic-Based Forecasting Method For Time Series Datasets
Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 2023 In this paper, a new probabilistic technique (a variant of Multiple Model Particle Filter-MMPF) will be used to predict time-series datasets. At first, the reliable performance of our method is proved using a virtual random scenario containing sixty ...
Abdullatif Baba
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Development and Validation of a Rule-based Time Series Complexity Scoring Technique to Support Design of Adaptive Forecasting DSS [PDF]
, 2016 Evidence from forecasting research gives reason to believe that understanding time series complexity can enable design of adaptive forecasting decision support systems (FDSSs) to positively support forecasting behaviors and accuracy of outcomes.
Adya, Monica, Lusk, Edward J.
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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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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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Computer Sciences & Mathematics ForumEffective forecasting is vital in various domains as it supports informed decision-making and risk mitigation. This paper aims to improve the selection of appropriate forecasting methods for univariate time series.
Leonard Dervishi +2 more
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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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Forecasting time series by means of evolutionary algorithms [PDF]
, 2004 Proceeding of: 8th International Conference in Parallel Problem Solving from Nature - PPSN VIII , Birmingham, UK, September 18-22, 2004.The time series forecast is a very complex problem, consisting in predicting the behaviour of a data series with only ...
C.Z. Janikow +8 more
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, 2015 In this chapter four combinations of input features and the feedforward, cascade forward and recurrent architectures are compared for the task of forecast tourism time series. The input features of the ANNs consist in the combination of the previous 12 months, the index time modeled by two nodes used to the year and month and one input with the daily ...
Teixeira, João Paulo +1 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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