in stock forecasting. Neural networks are viewed as one of the more suitable techniques. In this study, an experiment on … the forecasting of the Stock Exchange of Thailand (SET) was conducted by using feedforward backpropagation neural networks … neural network models in the forecasting of SET. Several global and local factors influencing the Thai stock market were used …

Forecasting network data traffic is an important part of the function of planning and managing information systems … forecasting China west railway Transportation Management Information Systems (TMIS) network traffic. The predictive results …

In this paper, we present an analysis of the results of a study into wholesale (spot) electricity price forecasting … accuracy of electricity price forecasting models. The efficiency of NN and SVM retraining for price forecasting was evaluated … December 1998. The analysis of the results showed that SVMs with one unique solution, produce more consistent forecasting …

Forecasting category or industry sales is a vital component of a company’s planning and control activities. Sales for … varying model significantly outperformed previous models both in terms of fitting and forecasting the sales data. …

Numerous econometric models have been proposed for forecasting property market performance, but limited success has …

forecasting methods employ cumulative production volume instead of time as the crucial explanatory variable, following Wright … work goes beyond identifying the most relevant factors in cost innovation. Our goal is to provide practical forecasting … information technology, Technological Forecasting & Social Change, 73 (2006) 1061-1083. H. Koh, C.L. Magee, A functional approach …