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 …

River stage forecasting is an important issue in water resources management and real-time prediction of extreme floods …. The present study investigates the performance of the wavelet regression (WR) technique in daily river stage forecasting … = 0.024, R = 0.969 in the validation stage performed better in forecasting daily river stages than the best accurate ANN …

This paper aims to explore the forecasting accuracy of RON/USD exchange rate structural models with monetary …

forecasting tools for regional employment growth. Because of relevant differences in data availability between the former East and …