The rest of this paper is organized as follows. Section 2 describes traditional System Identification and introduces the use of Particle Swarm Optimization (PSO) for determining the coefficients of a simple autoregressive moving average model (SwARMA). Section 3 explains Particle Swarm Optimization. Section 4 describes the results of using PSO for determining the ARMA model parameter (SwARMA) f...

In this paper we consider the forecasting performance of a range of semiand non-parametric methods applied to high frequency electricity price data. Electricity price time-series data tend to be highly seasonal, mean reverting with price jumps/spikes and timeand price-dependent volatility. The typical approach in this area has been to use a range of tools that have proven popular in the financi...

This study presents an application of neural network methods for forecasting per pupil expenditures in public elementary and secondary schools in the United States. Using annual historical data from 1959 through 1990, forecasts were prepared for the period from 1991 through 1995. Forecasting models included the multivariate regression model developed by the National Center for Education Statist...

in this paper, lift and drag coefficients were numerically investigated using numeca software in a set of 4-digit naca airfoils. two metamodels based on the evolved group method of data handling (gmdh) type neural networks were then obtained for modeling both lift coefficient (cl) and drag coefficient (cd) with respect to the geometrical design parameters. after using such obtained polynomial n...

in this paper, a model based on gmdh type neural network, is used to predict gas price in the spot market while using oil spot market price, gas spot market price, gas future market price, oil future market price and average temperature of the weather. the results suggest that gmdh neural network model, according to the root mean squared error (rmse) and direction statistics (dstat) statistics ...

Residential sector is one of the energy-consuming districts countries that causes CO2 emission in large extent. In this regard, must be considered energy policy making related to reduction and other greenhouse gases. present work, residential three countries, including Indonesia, Thailand, Vietnam Southeast Asia, are discussed modeled by employing Group Method Data Handling (GMDH) Multilayer Pe...

Recently, a lot of attention has been devoted to advanced techniques of system modeling. PNN(polynomial neural network) is a GMDH-type algorithm (Group Method of Data Handling) which is one of the useful method for modeling nonlinear systems but PNN performance depends strongly on the number of input variables and the order of polynomial which are determined by trial and error. In this paper, w...