This paper focuses on the methodology used in applying the Time Series Data Mining techniques to financial time series data for calculating currency exchange rates of US dollars to Indian Rupees. Four Models namely Multiple Regression in Excel, Multiple Linear Regression of Dedicated Time Series Analysis in Weka, Vector Autoregressive Model in R and Neural Network Model using NeuralWorks Predic...

In this paper, the support vector regression (SVR) methodology was adopted to estimate the horizontal global solar radiation (HGSR) based upon sunshine hours (n) and maximum possible sunshine hours (N) as input parameters. The capability of two SVRs of radial basis function (rbf) and polynomial basis function (poly) was investigated and compared with the conventional sunshine duration-based emp...

Erratum Following publication of the original article [1] the authors contacted the team with the request that some additional information be added to the article. Please see below for details: Additional Table: absolute variability Variability (VAR) presented in the main article represents mean variability between test and retest, not absolute variability as stated. The authors would like to a...

To effectively predict auto sales and improve the competitiveness of automotive enterprise, the characteristics of actual auto sales were analyzed, owing to the seasonal fluctuations and the nonlinearity of monthly sales, the combination forecasting model based on seasonal Index and RBF neural network was proposed. The weights of the two single models were computed using mean absolute percentag...

â  the prediction of maximum temperatures as one of the most important climatic parameters due to climate change, global warming and the recent drought will provide definitely more opportunity for planning and the provision of necessary arrangements for the planners. maximum temperatures are much important in management of natural and water resources, agriculture, development of pests and disea...