time series forecasting problems
Dimensionality Reduction for Time Series Decoding and Forecasting Problems
... Abstract. The paper is devoted to the problem of decoding multiscaled time series and forecasting. The goal is to recover the dependence between an input signal and a target response. The proposed ...
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An Industrial Application of Time Series Forecasting of Lumber Demand.
... several problems with this forecasting ...The time-series analyses in this paper show that all the skus studied demonstrate marked seasonal ...weekly time series plots and ...
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Nonparametric Risk Bounds for Time-Series Forecasting
... classification problems with independent and identically distributed ...to time-series models, so that economic and financial forecasting techniques can be evaluated ...
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Cross temporal aggregation: Improving the forecast accuracy of hierarchical electricity consumption
... and forecasting several connected time series. In most problems related with energy conservation, management and pricing, any decision taken is multi-layered, con- sidering and affecting ...
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Performance evaluation of series and parallel strategies for financial time series forecasting
... for time series ...introduced series and parallel combination methodologies to con- nect the components of hybrid ...important forecasting models that have been successfully applied in ...
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Estimation and Model Selection for Time Series Forecasting
... its time of occurrences is called time series and hence time is one of the key variables in time series ...in time leads to new and unique problems in statistical ...
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Time Series Forecasting Using Fuzzy Time Series With Hedge Algebras Approach
... of forecasting problems, because Hedge algebras are considered as an algebraic approach to the inherent word semantics and word-domains of each individual linguistic variable, which is simply understood as ...
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Forecasting Inflation using Functional Time Series Analysis
... In forecasting inflation many efforts have been made using different vari- ables and ...of time series methodologies we found that Wiener (1964) had pioneer work ,which laid the foundation of modern ...
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Time Series Forecasting with Missing Values
... a time series can be defined as a series of observations taken successively every equally spaced time ...of time series prediction is to forecast the future trend of the data ...
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A Modified Approach on Fuzzy Time Series Forecasting
... the time series comprised of imprecise ...of time series the uncertainty of the individual observed values as well as the interpretation of a sequence of uncertain observed values are of ...
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Neural Networks In Business Time Series Forecasting: Benefits And Problems
... Hoptroff et al. (1991) found that NNs trained by the concurrent descent technique outperformed linear regression when the available data was sparse or noisy. Hansen & Nelson (1997) applied a genetic algorithm (GA) to ...
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Vol 2013
... fuzzy time series was proposed by Song and Chissom ...the time invariant model and the time variant model for dealing with forecasting ...with forecasting problems using ...
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Hedge Algebra Approach for Fuzzy Time series To Improve Result Of Time Series Forecasting.
... Fuzzy time series was first introduced by Song and Chissom [1], it is considered as the set of linguistic values that is observed by the ...conventional time series are quantitative view about ...
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Energy Management through Cost Forecasting for
... Time series forecasting techniques such as exponential smoothing models and the ARIMA.. 76.[r] ...
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Time-Series analysis for wind speed forecasting
... In this paper we have identified the comparative study of ARIMA and ETS models which match for the measurement of wind speed time-series. The model(2, 1, 1) exhibits the best performance. The confirmation ...
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A Comparative Simulation Study of ARIMA and Fuzzy Time Series Model for Forecasting Time Series Data
... a forecasting method is quite rapidly resulting, there are many choices of methods that can be used to forecast time series data according to needs of the ...of forecasting future events of a ...
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Automating Analytics: Forecasting Time Series in Economics and Business
... We now proceed to compare the MF projections with the ones, generated by the optimal Auto ARIMA models. Relevant accuracy metrics for the two sets of forecasts are presented in Table 3. All the indicators of accuracy ...
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Machine Learning Models for Sales Time Series Forecasting
... with a long time period (2 years) for a specific store, Figure 11 shows the forecast in the case of historical 79. data with a short time period (3 days) for the same specific store[r] ...
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Time Series Forecasting using a Two-level Multi-
... The fitness function is based on the ARIMA model for the forecasting of time series cost data 189.. objects individually, as seen in the equation below.[r] ...
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Modeling and Forecasting Africa's GDP with Time Series Models
... The main objective of this study is to model and forecast the Gross Domestic Product of Africa using Time Series models. In the study, we present the largest economy of Africa by regions and give a macro ...
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