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39 results for “forecast accuracy”
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Research ArticleOpen accessIn the abstractElectricity Load Forecasting based on Framelet Neural Network TechniqueMohammed K. AbdLoad forecasting is very essential to the operation of electricity companies. It enhances the energy-efficient and reliable operation of a power system. This study shows Electricity Load Forecasting modeling based on Framelet Neural Network Technique (FNN) for Baghdad City. Framelet technique is implemented to the time series data, decomposing the data into number of Framelet coefficient signals. The decomposed signals … …American Journal of Applied Sciences, Vol. 6, Issue 5 · 31 May 2009 · 8,278 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting Foreign Direct Investment Inflow in Jordan: Univariate ARIMA ModelAl-Abdulrazag Bashier, Bataineh TalalThe present study is an attempt to build a Univariate time series model to forecast the FDI inflows into Jordan over the coming period 2004-2025. The study employs Box-Jenkins methodology of building ARIMA (Autoregressive Integrated Moving Average) model to achieve the goals of the study. An annual sample time series data for the FDI in Jordan was utilized over the … …Journal of Social Sciences, Vol. 3, Issue 1 · 31 Mar 2007 · 8,389 accessesView PDFCite
Research ArticleOpen accessIn the abstractHydrological Forecasting Using Hybrid Data-Driven ApproachYoungmin Seo, Sungwon KimThis study develops a hybrid model, EEMD-FANN, coupling feed Forward Artificial Neural Network (FANN) and Ensemble Empirical Mode Decomposition (EEMD) for improving the accuracy of daily river stage forecasting. An original river stage data is broken down into a residue and Intrinsic Mode Functions (IMFs) using the EEMD and different FANNs are developed as forecasting models for the decomposed IMFs … …American Journal of Applied Sciences, Vol. 13, Issue 8 · 2 Sep 2016 · 8,140 accessesView PDFCite
Research ArticleOpen accessIn the abstractPartial Least Squares Regression Based Variables Selection for Water Level PredictionsNoraini Ibrahim, Antoni WibowoFloods are common phenomenon in the state of Kuala Krai, specifically in Kelantan-Malaysia. Every year, floods affecting biodiversity on this region and also causing property loss of this residential area. The residents in Kelantan always suffered from floods since the water overflows to the areas adjoining to the rivers, lakes or dams. Months, average monthly rainfall, temperature, relative humidity and … …American Journal of Applied Sciences, Vol. 10, Issue 4 · 7 Apr 2013 · 6,624 accessesView PDFCite
Research ArticleOpen accessIn the abstractOnline Forums Hotspot Prediction Based on Sentiment AnalysisK. Nirmala Devi, V. Murali BhaskarnProblem statement: Online forums hotspot prediction is one of the significant research areas in web mining, which can help people make proper decision in daily life. Online forums, news reports and blogs, are containing large volume of public opinion information. Rapid growth of network arouses much attention on public opinion, it is important to analyse the public opinion in time … …Journal of Computer Science, Vol. 8, Issue 8 · 11 Jul 2012 · 7,363 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting and Modelling Electricity Demand Using Anfis PredictorM. Mordjaoui, B. BoudjemaProblem statement: Load forecasting plays an important task in power system planning, operation and control. It has received an increasing attention over the years by academic researchers and practitioners. Control, security assessment, optimum planning of power production required a precise short term load forecasting. Approach: This study tries to combine neural network and fuzzy logic for next week electric load … …Journal of Mathematics and Statistics, Vol. 7, Issue 4 · 14 Sep 2011 · 7,817 accessesView PDFCite
Research ArticleOpen accessIn the abstractDesign and Implementation of Novel Artificial Neural Network Based Stock Market Forecasting System on Field-Programmable Gate ArraysMd. Syedul Amin, Md. Mamun, Fazida Hanim Hashim et al.Problem statement: Multiagent system is very proficient and has rules well-suited for financial forecast with its neural network. In financial forecasting, the approach for rules extractions is less pertinent and involves algorithms which are complex. The unsupervised network method lacks in comprehensibility and leads to ambiguity. Approach: The application of neural network technology to real-time processing of financial market analysis … …American Journal of Applied Sciences, Vol. 8, Issue 10 · 12 Sep 2011 · 7,634 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntegrated Modeling for Flood Hazard Mapping Using Watershed Modeling SystemSeyedeh S. Sadrolashrafi, Thamer A. Mohamed, Ahmad R.B. Mahmud et al.In this stduy, a new framework which integrates the Geographic Information System (GIS) with the Watershed Modeling System (WMS) for flood modeling is developed. It also interconnects the terrain models and the GIS software, with commercial standard hydrological and hydraulic models, including HEC-1, HEC-RAS, etc. The Dez River Basin (about 16213 km2) in Khuzestan province, IRAN, is domain of study … …American Journal of Engineering and Applied Sciences, Vol. 1, Issue 2 · 30 Jun 2008 · 10,799 accessesView PDFCite
Research ArticleOpen accessIn the abstractEstimation Techniques for Monitoring and Controlling the Performance of the Computer Communication NetworksIbrahiem M.M. El Emary, Adanan I. Al RabiaThis study was concerned with making a comparative study between four types of time series model with the goal of choosing the optimum one to predict the performance of a computer communication network. The investigated four types of time series are: Least Square (LS), Fourier series, Exponential Weighted Moving Average (EWMA) and the Auto Regressive Integrated Moving Average (ARIMA). Comparative … …American Journal of Applied Sciences, Vol. 2, Issue 10 · 31 Oct 2005 · 7,131 accessesView PDFCite