We study the autocorrelation structure of aggregates from a continuous-time process. The underlying continuous-time process or some of its higher derivative is assumed to be a stationary continuous-time auto-regressive fractionally integrated moving-average (CARFIMA) process with Hurst parameter H. We derive closed-form expressions for the limiting autocorrelation function and the normalized sp...

In this paper, we investigate the robustness of Feed Forward Neural Network (FFNN) ensemble models applied to quarterly time series forecasting tasks, by comparing their prediction ability with that of Seasonal Auto-regressive Integrated Moving Average (SARIMA) models. We obtained adequate SARIMA models which required statistical knowledge and considerable effort. On the other hand, FFNN ensemb...

Time series data mining (TSDM) techniques explores large amount of time series data in search of interesting relationships among variables. The TSDM methods overcome limitations including stationarity and linearity requirements of traditional time series analysis by adapting data mining concepts for analyzing time series data. The Feed Forward Neural Net is one of the most widely used neural ne...

This paper presents the adaptation of CORBFN, an evolutionary cooperative-competitive hybrid algorithm for the design of Radial Basis Function Networks, for short-term forecasting of the price of extra virgin olive oil. In the proposed cooperative-competitive environment, each individual represents a Radial Basis Function, and the entire population is responsible for the final solution. In orde...

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This paper deals with the application of the Multi Objective Generalized Predictive Control (MOGPC) to level control in a laboratory process. The major characteristic of the considered plant is that the manual draining vane can take many positions causing changes in plant dynamics and strong disturbances in the process. The controller is based on a set of Controlled Auto Regressive Integrated M...

Wide-spread real-time applications make it necessary for service providers to guarantee QoS parameters. This requires precise forecast of network traffic. A possible method of the forecast is measuring traffic then analyzing it and fitting model to the measured data, finally predicting the observed parameter using the fitted model. The efficiency of the prediction is decreased by outlying sampl...

In this paper an adaptation of CO2RBFN, evolutionary COoperativeCOmpetitive algorithm for Radial Basis Function Networks design, applied to the prediction of the extra-virgin olive oil price is presented. In this algorithm each individual represents a neuron or Radial Basis Function and the population, the whole network. Individuals compite for survival but must cooperate to built the definite ...