Pattern recognition to forecast seismic time series

Day-ahead Price Forecasting of Electricity Markets by a New Hybrid Forecast Method

Energy price forecast is the key information for generating companies to prepare their bids in the electricity markets. However, this forecasting problem is complex due to nonlinear, non-stationary, and time variant behavior of electricity price time series. Accordingly, in this paper a new strategy is proposed for electricity price forecast. The forecast strategy includes Wavelet Transform (WT...

Seismic Data Forecasting: A Sequence Prediction or a Sequence Recognition Task

In this paper, we have tried to predict earthquake events in a cluster of seismic data on pacific ring of fire, using multivariate adaptive regression splines (MARS). The model is employed as either a predictor for a sequence prediction task, or a binary classifier for a sequence recognition problem, which could alternatively help to predict an event. Here, we explain that sequence prediction/r...

A Comparison Between Time Series, Exponential Smoothing, and Neural Network Methods To Forecast GDP of Iran

Financial time series forecasts using fuzzy and long memory pattern recognition systems

In this paper, the concept of long memory systems for forecasting is developed. The Pattern Modelling and Recognition System (PMRS) and Fuzzy Single Nearest Neighbour (SNN) methods are introduced as local approximation tools for forecasting. Such systems are used for matching current state of the time-series with past states to make a forecast. In the past, the PMRS system has been successfully...

Price forecast in the competitive electricity market by support vec - tor

Price forecast is a task challenging and very important in competitive electricity market context. Both market players and regulators concern very much about the price evolution, on one hand, the prediction of the market price is a crucial information for the production arrangement and bidding strategies. On the other hand, the regulators need to analyze the market behavior and monitor the mark...