Using the SOM and Local Models in Time-Series Prediction
نویسنده
چکیده
In this paper we test the Self-Organizing Map (SOM) on the problem of predicting chaotic time-series (speciically Mackey-Glass series) with local linear models deened separately for each of the prototype vectors of the SOM. We see that the method achieves good results. This together with the capabilities of the SOM make it a valuable tool in exploratory data mining.
منابع مشابه
Publication 1 Using the SOM and Local Models in Time−Series Prediction
In this paper we test the Self-Organizing Map (SOM) on the problem of predicting chaotic time-series (speci cally Mackey-Glass series) with local linear models de ned separately for each of the prototype vectors of the SOM. We see that the method achieves good results. This together with the capabilities of the SOM make it a valuable tool in exploratory data mining.
متن کاملEvaluation of Univariate, Multivariate and Combined Time Series Model to Prediction and Estimation the Mean Annual Sediment (Case Study: Sistan River)
Erosion, sediment transport and sediment estimate phenomenon with their damage in rivers is a one of the most importance point in river engineering. Correctly modeling and prediction of this parameter with involving the river flow discharge can be most useful in life of hydraulic structures and drainage networks. In fact, using the multivariate models and involving the effective other parameter...
متن کاملAvailability Prediction of the Repairable Equipment using Artificial Neural Network and Time Series Models
In this paper, one of the most important criterion in public services quality named availability is evaluated by using artificial neural network (ANN). In addition, the availability values are predicted for future periods by using exponential weighted moving average (EWMA) scheme and some time series models (TSM) including autoregressive (AR), moving average (MA) and autoregressive moving avera...
متن کاملSome New Methods for Prediction of Time Series by Wavelets
Extended Abstract. Forecasting is one of the most important purposes of time series analysis. For many years, classical methods were used for this aim. But these methods do not give good performance results for real time series due to non-linearity and non-stationarity of these data sets. On one hand, most of real world time series data display a time-varying second order structure. On th...
متن کاملEvaluation of SARIMA time series models in monthly streamflow estimation in Idanak hydrometry station
prediction of hydrological variables is a highly effective tool in water resource management. One of the important tools for modeling hydrological processes is the use of time series modeling and analysis. River series production series can be used by time series models in various studies such as drought, flood, reservoir systems design and many other purposes For this purpose, monthly flow dat...
متن کامل