forecasting corporate credit ratings from financial statement data.Design/methodology/approach – The ANN model used in the study …

activity. The objective of this research is to develop a distribution short-term load forecasting technology consisting of a … forecasting method, development methodology, theories necessary to support required technical components, and the hardware and …

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 …

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 …

Time series forecasting is an important area of forecasting in which past observations of the same variable are … models, autoregressive (AR) techniques, moving averages (MA) etc. Recent research activities in forecasting also suggested … that artificial neural networks can be used as an alternative to traditional linear forecasting models. This study will …

combinatory procedures as forecasting techniques to improve the predictive accuracy of hog price outlook forecasts. Many of these … forecasting techniques have never been applied to livestock markets. Quarterly data from the mid- to late-1970s through 2007 for … improving Iowa’s price forecasting performance via composite procedures.Finally, given the potential benefits of forecast …