Time Series Forecasting
A Neural Network Approach to Time Series Forecasting
... the time series ...heterogeneous forecasting models adequate to local ...the time series forecasting ...smallest forecasting error but does not accurately forecast the ...
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Agent-based distributed time series forecasting system
... distributed time series forecasting approach based on the modified Group Method Data Handling (GMDH) method and agent oriented programing is ...the time series of EUR/USD currency pair ...
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A New Approach for Time Series Forecasting: Bayesian Enhanced by Fractional Brownian Motion with Application to Rainfall Series
... different forecasting techniques for a class of high roughness long-term time series ...The series were selected regarding the long or short term stochastic dependence of the time ...
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Time Series Forecasting of Energy Commodity using Grey Wolf Optimizer
... the forecasting of commodity prices. In this study, a forecasting model based on a relatively new Swarm Intelligence (SI) behaviour, namely Grey Wolf Optimizer (GWO), is developed for short term time ...
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Fuzzy Time Series Forecasting based on Grey Model and Markov Chain
... The rest of the article is organized as follows. In Section 2, we provide the parameter estimators based on accumulation method (AM) and prove some of its properties. In Section 3, the transformation processes of the ...
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Time Series Forecasting by using Seasonal Autoregressive Integrated Moving Average: Subset, Multiplicative or Additive Model
... ARIMA is the method first introduced by Box and Jenkins (1976) and until now become the most popular models for forecasting univariate time series data. This model has been originated from the ...
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A short-term data based water consumption prediction approach
... classical time series forecasting ...our time series contained two principal seasonalities that were weekly and annual, one-minute frequency data would yield ARIMA orders of 10,800 (in ...
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APPLYING THE ARTIFICIAL NEURAL NETWORK METHODOLOGY FOR FORECASTING THE TOURISM TIME SERIES
... in time series ...and forecasting tool in business applications [3, 4, ...in forecasting because a neural network is better able to recognize the high-level features, such as serial ...
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An Artificial Neural Network for Data Forecasting Purposes
... for time series forecasting based on flexible multi-layer feed-forward ...stochastic time effective neural network to develop a forecasting model of global stock ...
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Fault Detection of Computer Communication Networks Using an Expert System
... alarms. Time series have been implemented to perform forecasting in many ...the time series in computer network management in view point of performance ...monitoring. Time ...
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Using Artificial Neural Networks to generate trading signals for crude oil, copper and gold futures
... financial time series forecasting now often favours more advanced optimization procedures over simple backpropagation / gradient descent learning algorithms such as combined GA/ANN approaches (Kim ...
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A Survey Paper on Crime Prediction Technique Using Data Mining
... Fuzzy time series forecasting was originally originate by Song & ...a series of papers to forecast student enrolments at the University of ...Fuzzy time series models ...
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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, ...improving time series forecasting ...
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Cad. Saúde Pública vol.27 número9
... This study aimed to develop a forecasting model for the incidence of dengue in Ribeirão Preto, São Paulo State, Brazil, using time series analysis. The model was performed using the Seasonal Autore- ...
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The role of no-arbitrage on forecasting: lessons from a parametric term structure model
... the forecasting analysis, we propose a careful analysis of the risk premium structure, which should be particularly interesting for portfolio managers and risk managers, as a complementing ...
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Seasonal ARIMA for Forecasting Air Pollution Index: A Case Study
... study, time series models will be discussed to analyze future air quality and used in modeling and forecasting monthly future air quality in ...Conclusion: Time series model used in ...
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2 Structural Time Series Models
... frequency time series, have fostered the use (and development) of statistical and econometric techniques to treat them more ...structural time series models by which a time ...
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Performance of Exchange Rate Forecast Using Distance-Based Fuzzy Time Series
... various forecasting problems such as university enrolment [7], [8], [9] direct tax collection [10], stock index [11], [12], [13] and temperature ...fuzzy time series model in order to get a better ...
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Tourism Time Series Forecast - Different ANN Architectures with Time Index Input
... The behaviour of the series indicates that there is seasonality (higher values during the summer months and lower values in winter). It is also clear that there is a progressive trend over the period in question. ...
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