Forecasting Methods
PREDICTING KAPPA NUMBER IN A KRAFT PULP CONTINUOUS DIGESTER: A COMPARISON OF FORECASTING METHODS
... predicting methods. Four different methods were compared considering accuracy of the ...statistical forecasting indexes evaluated, followed by MLR, ANN and ...
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Foreword 'Advances in flood forecasting'
... flash-flood forecasting methods, and use of radar for now-casting and hydrological ...and methods to end users, such as water management bodies and civil protection authorities, to ensure rapid flood ...
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Forecasting Subnational Monthly Births and Deaths using Seasonal Time Series Methods
... appropriate forecasting methods must be ...the forecasting performance of seasonal ARIMA, Holt-Winters and State Space models applied to birth and death monthly forecasting by sex and NUTS 3 ...
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A selecção de indicadores no estudo prospectivo “Forecasting
... certain forecasting methods as well as to choose the methods that could not be used throughout the development of the work, contributed to the strength of the list of ...
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A Comparison on Statistical Methods and Long Short Term Memory Network Forecasting the Demand of Fresh Fish Products
... statistical methods implementation in this study are univariate. Univariate methods use only a single variable as input and most likely, the variable of input will be the output as ...univariate ...
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Forecasting electricity prices
... price forecasting methods have been recently proposed to counter the above-mentioned problems ...these methods is their ability to infer hidden relationships in ...these methods still have ...
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Modelling and Forecasting Mortality Patterns
... Understanding mortality dynamics over the age and time dimensions is crucial for any demographic analysis. Towards this end, it is important to look at the historical time series data from different perspectives and to ...
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Artificial Neural Networks versus Box-Jenkins Methodology in Tourism Demand Analysis
... classical forecasting methods, providing a response to situations that would be difficult to treat through classical methods (Thawornwong & Enke, ...series forecasting through the analysis ...
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Forecasting human entrances at a commercial store using facial recognition data
... Both), forecasting periods ...several forecasting methods were tested: conventional time series methods and time series models based on machine learning; a regression approach ...Such ...
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Forecasting small population monthly fertility and mortality data with seasonal time series methods
... allow forecasting of data with time ...smoothing methods. The ability of these methods to model complex structures of temporal interdependence observed in the data has been tested, but their ...
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Forecasting telecommunication new service demand by analogy method and combined forecast
... The usual approach to forecasting involves choosing a forecasting method among several candidates and using that method to derive forecasts. However, forecasts from one given method may provide some useful ...
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ANA SOFIA FIDALGO DIAS, 323 A Project carried out on the Finance course, under the supervision of: Miguel Ferreira Patricia Relvas
... Dynamic Forecasting Process, implemented within the organization as a way of reengineering its performance management concept and processes, so as to make it more flexible and capable to react to volatile business ...
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Load Forecasting DOCEIS'16
... The recognition of future electricity consumption patterns is an important part of the planning, operation and exploration of Electrical Power System. The quality control of Power Systems and effectiveness of its ...
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Multi-model data fusion for river flow forecasting: an evaluation of six alternative methods based on two contrasting catchments
... produce forecasting outputs that are more accurate than (i) individual models or (ii) simple arithmetic operations and weighted statistical functions (Shamseldin et ...
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Does curvature enhance forecasting?
... in forecasting related exercises (see Duffee, 2002; Almeida and Vicente, ...A forecasting empirical application adopting high frequency (daily) Brazilian fixed income data indicates that our model ...
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The Balance Model of Regional Development Management in Certain Territorial Conditions: Development and Application
... As to public governance, these models and related software packages exhibit certain limitations that lie in their content being unsuitable for meeting the needs of the development of specific mechanisms and tools to ...
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NEW APPROACH OF THE ANN METHODOLOGY FOR FORECASTING TIME SERIES: USE OF TIME INDEX
... In previous publications, the authors reported their work with the artificial neural networks (ANN) methodologies for the forecast of guest nights in hotels time series. The ANN methodology has made predictions more ...
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Autoencoders: application to forecasting
... In the models D.1 through D.8 the number of maximum iterations was reduced to 50 (from 150 in the previous models) because with the increase of the autoencoder complexity, 48 neurons in the input and output layers, and ...
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A self-adaptive evolutionary fuzzy model for load forecasting problems on smart grid environment
... load forecasting has been increasing lately and improving the use of energy resources remains a great ...short-term forecasting over microgrids and large-grids, being able to accurately predict data in ...
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Airport Performance Analysis and Forecasting
... Decomposition methods have also seen several applications in air passengers demand ...longer-term forecasting (2–5 years)” [62, ...improves forecasting performance for long lead-times, by damping the ...
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