Methods of demand forecasting
Demand forecasting in a multi-specialty hospital setting: a comparative study of machine learning and classical statistical methods
... up of the algorithms: Linear Regression, Neural Network, Regression Tree, Gradient Boost- ing Regression Tree, Support Vector Machines and Gaussian ...data of sales of LCDs (Liquid Crystal Display) ...
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Committee machines for hourly water demand forecasting in water supply systems
... case of ELMs in which some parameters do not need to be ...variant of ANNs that uses fuzzy inference, which is powerful in approaching hybrid methodologies for parameter ...GMDH methods split a ...
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Forecasting telecommunication new service demand by analogy method and combined forecast
... problems of forecasting market demand for a new service or ...absence of historical data in this new ...the forecasting work ...some methods to solve or avoid this predicament, ...
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Forecasting tourism demand for Lisbon´s region : a data mining approach
... quality of historical data is not enough or even when the need for a decision is so urgent that there is not enough time to calculate ...lack of consistency, optimism, wishful thinking or political ...
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Energetic analysis of water supply systems: demand forecasting using artificial intelligence techniques
... performance of the 99 models designed was ...influence of these two parameters, fixing one of them and varying the ...periodicities of 12, 24, 48 and 168 ...SVR methods in every ...
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Intermittent demand forecasting for aircraft inventories: a study of Brazilian’s Boeing 737NG aircraft´s spare parts management
... relevance of the discussed topic, we created predictions using the prediction methods known as Croston, Winters, Weight Moving Average, Single Exponential Smooth and Poisson for 53 intermittent ...
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Enhanced water demand analysis via symbolic approximation within an epidemiology-based forecasting framework
... One of the main hypotheses of this paper is to combine these similarity patterns between DMAs with those obtained from MI ...predictive methods based on available historical data by using information ...
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Métodos de previsão: estudo de caso no setor de transporte de uma Universidade Federal/ Forecasting methods: case study in the transport sector of a Federal University
... Demand forecasting is of considerable importance for the effectiveness of the logistics process, making organizational planning and decision making more ...number of requests for ...
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Forecasting electricity demand using generalized long memory
... year of 1999, the difference being that the SARIMA fares better also in the sixth hour for steps ahead higher than ...MAPEs of 3,12% in 1999 and 3,93% in ...speak of h steps ahead, we consider the ...
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A Comparison on Statistical Methods and Long Short Term Memory Network Forecasting the Demand of Fresh Fish Products
... point of the LSTM model, is also is ...accuracy of the current ...downside of this, is that being so variable dependent, not only the model must be maintained, but also all the sources of this ...
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Análise de métodos de previsão de demanda de séries temporais: estudo de caso em uma empresa fabricante de máquinas e equipamentos eletromecânicos / Analysis of time series demand forecasting methods: a case study in a company that manufactures electromechanical machines and equipment
... Diante deste contexto, este trabalho tem por objetivo identificar o método de previsão de demanda mais adequado para realizar previsões baseadas em séries temporais para um[r] ...
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Long-range forecasting of intermittent streamflow
... layers of the catchments, it is clear that for the occurrence of monthly flow the larger scale climatic layer is influential, while for the intensity of monthly flow local catchment pro- cesses and ...
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Microfounded forecasting
... set of 298 registered institutions in the system, with a smaller active group of around 100 in- ...forecasts of monthly IPCA in‡ation from January, 2nd, 2006, to June 7th, 2018 (3; 165 working ...
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Microfounded forecasting
... main methods to forecast in‡ation: time-series models of the ARIMA variety; structural models built upon the Phillips Curve; methods using information embedded in asset prices – in particular, the ...
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Probabilistic methods for seasonal forecasting in a changing climate: Cox-type regression models. - Portal Embrapa
... Managers of climate-sensitive industries can incorpo- rate probabilistic forecasts into their decision-making as long as the associated uncertainties are clearly spelled out (Nelson et ...consequences of ...
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Forecasting small population monthly fertility and mortality data with seasonal time series methods
... amount of research has focused on the development and application of time series models in population forecasts, focusing either on total population growth or on individual components of growth (see, ...
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Volatility forecasting : the role of financial news in forecasting stock market volatility
... First of all, we run two univariate models: one using the number of news and the other using the implied volatility in the previous ...an of 82,7%, mostly because of the strong autocorrelation ...
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Proposta de uma sistemática para previsão de demanda aeroportuária = um estudo ex-post-facto = Proposal of a systematic forecasting for an airport demand: an ex-post-facto study
... development of several components of the airport system relies on the levels of activity foreseen for the ...distribution of the demand for its several ...the demand in the last ...
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The importance of online tourism demand
... analysis of tourism demand without considering the technological environment that characterizes the society, to which the tourism sector is extremely sensitive, appears to be reductive and does not ...
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Assessment of acute physiological demand for soccer.
... activity of high intensity and long duration, in which movements that re- quire great strength and speed, such as jumps and sprints, result in high levels of muscle microtrauma, hampering athletes’ training ...
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