EditorialOpen accessIn the abstractNew Kind of Statistical MethodsCagdas Hakan AladagAladag, C.H. and E. Egrioglu, 2012. Advanced Time Series Forecasting Methods. In: Advances in Time Series Forecasting, Aladag, C.H. and E. Egrioglu (Eds.), Bentham Science Publishers, Oak Park, ISBN-10: 1608053733. Aladag, C.H., 2011. A Hybrid Intelligent Technique Combines Neural Networks and Tabu Search Methods for Forecasting, Computer Search Algorithms. 1st Edn., Nova Publisher, ISBN: 978-1-61209-043-6. Aladag, C.H., E Egrioglu, U. … …Journal of Mathematics and Statistics, Vol. 10, Issue 4 · 28 Nov 2014 · 7,588 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of Neuro-Fuzzy Techniques for Solar RadiationW. A. Rahoma, U. Ali Rahoma, A. H. HassanProblem statement: The prediction is very useful in solar energy applications because it permits to estimate solar data for locations where measurements are not available. The developed artificial intelligence models predict the solar radiation time series more effectively compared to the conventional procedures based on the clearness index. Approach: The forecasting ability of some models could be further enhanced with … …Journal of Computer Science, Vol. 7, Issue 10 · 11 Aug 2011 · 7,077 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Efficient Weather Forecasting System using Radial Basis Function Neural NetworkTiruvenkadam Santhanam, A. C. SubhajiniProblem statement: Accurate weather forecasting plays a vital role for planning day to day activities. Neural network has been use in numerous meteorological applications including weather forecasting. Approach: A neural network model has been developed for weather forecasting, based on various factors obtained from meteorological experts. This study evaluates the performance of Radial Basis Function (RBF) with Back Propagation (BPN) … …Journal of Computer Science, Vol. 7, Issue 7 · 28 Jun 2011 · 7,754 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting Daily Demand in Cash Supply ChainsMichael WagnerProblem statement: Previous studies focused on explaining the long run determinants of currency demand offering limited insight into the short-run determinants and co-variability of daily demand in cash supply chains. Approach: This study contrasted competing techniques of forecasting daily demand in cash supply chains in order to determine the overall performance and the potential of joint forecasting for integrated planning. … …American Journal of Economics and Business Administration, Vol. 2, Issue 4 · 28 Nov 2010 · 7,736 accessesView PDFCite
Research ArticleOpen accessIn the abstractSuitability of Volatility Models for Forecasting Stock Market Returns: A Study on the Indian National Stock ExchangeTrilochan Tripathy, Luis A. Gil-AlanaProblem statement: Measuring volatility is an important issue for stock market traders. Also, volatility has been used as a proxy for riskiness associated with the asset. This study aims to compare the different volatility models based on how well they model the volatility of the India NSE. Approach: The study has made use of five models which are Historical/Rolling Window … …American Journal of Applied Sciences, Vol. 7, Issue 11 · 8 Nov 2010 · 7,851 accessesView PDFCite
Research ArticleOpen accessIn the abstractSeasonal Time Series Data Forecasting by Using Neural Networks Multiscale Autoregressive ModelSuhartono, B. S.S. Ulama, A. J. EndhartaProblem statement: The aim of this research was to study further some latest progress of wavelet transform for time series forecasting, particularly about Neural Networks Multiscale Autoregressive (NN-MAR). Approach: There were three main issues that be considered further in this research. The first was some properties of scale and wavelet coefficients from Maximal Overlap Discrete Wavelet Transform (MODWT) decomposition, particularly … …American Journal of Applied Sciences, Vol. 7, Issue 10 · 31 Oct 2010 · 7,751 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting Gold Prices Using Multiple Linear Regression MethodZ. Ismail, A. Yahya, A. ShabriProblem statement: Forecasting is a function in management to assist decision making. It is also described as the process of estimation in unknown future situations. In a more general term it is commonly known as prediction which refers to estimation of time series or longitudinal type data. Gold is a precious yellow commodity once used as money. It was made … …American Journal of Applied Sciences, Vol. 6, Issue 8 · 31 Aug 2009 · 11,091 accessesView PDFCite
Research ArticleOpen accessIn the abstractShort-Term and Medium-Term Load Forecasting for Jordan's Power SystemI. Badran, H. El-Zayyat, G. HalasaSeveral electric power companies are now forecasting electric loads based on conventional methods. However, since the relationship between loads and factors influencing these loads is nonlinear, it is difficult to identify its nonlinearity by using conventional methods. Most of papers deal with 24-h-ahead load forecasting or next day peak load forecasting. These methods forecast the demand power by using forecasted … …American Journal of Applied Sciences, Vol. 5, Issue 7 · 31 Jul 2008 · 7,081 accessesView PDFCite
Research ArticleOpen accessIn the abstractData-Driven Forecasting Schemes: Evaluation and ApplicationsJosip Vrbanek Jr, Wilson WangA reliable multi-step predictor is very useful to a wide array of applications to forecast the behavior of dynamic systems. The objective of this paper is to develop a more robust data-driven predictor for time series forecasting. Based on simulation analysis, it is found that multi-step-ahead forecasting schemes based on step inputs perform better than those based on sequential inputs. … …Journal of Computer Science, Vol. 3, Issue 9 · 30 Sep 2007 · 6,565 accessesView PDFCite