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39 results for “Forecast Accuracy”
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Research ArticleOpen accessIn the abstractEfficiency and Forecast Performance of Commodity Futures MarketsBernardina Algieri, Matthias KalkuhlThe present study empirically investigates market efficiency and the potential factors of inefficiency in the main non-energy commodity futures markets: maize, soybeans and wheat. With efficient markets, futures prices can be used as commodity price forecasts, with inefficient markets futures prices are not able to predict spot prices. Technically, exploring the drivers of inefficiency means to assess the determinants of … …American Journal of Economics and Business Administration, Vol. 11, Issue 1 · 10 Jun 2019 · 8,375 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting the Number of Monthly Active Facebook and Twitter Worldwide Users Using ARMA ModelQasem Abu Al-Haija, Qian Mao, Kamal Al NasrIn this study, an Auto-Regressive Moving Average (ARMA) Model with optimal order has been developed to estimate and forecast the short term future numbers of the monthly active Facebook and Twitter worldwide users. In order to pickup the optimal estimation order, we analyzed the model order vs. the corresponding model error in terms of final prediction error. The simulation results … …Journal of Computer Science, Vol. 15, Issue 4 · 19 Apr 2019 · 8,599 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Use of Remote Sensing Techniques in Detecting and Predicting Forest Vegetation Change Using MODIS Satellite Data, Golestan, IranAkram Karimi, Sara Abdollahi, Hamid Reza Kabiri Balajadeh et al.It is so important to be aware of quantitative and qualitative characteristics of changes for the environment, land use planning and sustainable development. Detecting the changes in the condition of an issue is done by time difference observations. Change detection refers to the process of detecting time changes of an object through different time observations. The detection of changes by … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 1 · 30 Mar 2018 · 8,287 accessesView PDFCite
Research ArticleOpen accessIn the abstractBuilding Energy Modeling Using Artificial Neural NetworksMaya Arida, Nabil Nassif, Rand Talib, Taher Abu-LebdehAccurate modeling of total building energy is now vital to reduce energy consumption. This is especially true for buildings since they are considered as the largest energy consumer in the United States. This paper investigates modeling methods for building energy-systems using non-linear auto-regression artificial neural networks. The proposed model can forecast the whole building energy consumptions given the four input … …Energy Research Journal, Vol. 7, Issue 2 · 6 Jun 2017 · 7,125 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 · 8,136 accessesView PDFCite
Research ArticleOpen accessIn the abstractDAILY CRUDE OIL PRICE FORECASTING MODEL USING ARIMA, GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTIC AND SUPPORT VECTOR MACHINESRana Abdullah Ahmed, Ani Bin ShabriCrude oil price forecasting is gaining increased interest globally. This interest is due mainly to the economic value attached to the product. For this reason, new forecasting methods are proposed in the literature. This paper proposes a novel technique for forecasting crude oil price based on Support Vector Machines (SVM). The study adopts the data on crude oil price of … …American Journal of Applied Sciences, Vol. 11, Issue 3 · 11 Jan 2014 · 8,725 accessesView PDFCite
Research ArticleOpen accessIn the abstractBAYESIAN MODEL AVERAGING WITH MARKOV CHAIN MONTE CARLO FOR CALIBRATING TEMPERATURE FORECAST FROM COMBINATION OF TIME SERIES MODELSHeri Kuswanto, Mega Rahmatia SariGlobal warming is an important issue related to the climate and weather forecast. It is shown by significantly increasing the atmospheric temperature level. Hence, improving the forecast accuracy of temperature is an important issue. The forecast is commonly done by performing a deterministic forecast meaning that the system will generate a point forecast without taking into account the uncertainty induced … …Journal of Mathematics and Statistics, Vol. 9, Issue 4 · 29 Nov 2013 · 7,078 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 · 6,621 accessesView PDFCite
Research ArticleOpen accessIn the abstractParameters Estimate of Autoregressive Moving Average and Autoregressive Integrated Moving Average Models and Compare Their Ability for Inflow ForecastingMohammad Valipour, Mohammad Ebrahim Banihabib, Seyyed Mahmood Reza BehbahaniIn this study the ability of Autoregressive Moving Average (ARMA) and Autoregressive Integrated Moving Average (ARIMA) models in forecasting the monthly inflow of Dez dam reservoir located in Teleh Zang station in Dez dam upstream is estimated. ARIMA model has found a widespread application in many practical sciences. In addition, dam reservoir inflow forecasting is done by some methods such … …Journal of Mathematics and Statistics, Vol. 8, Issue 3 · 30 Aug 2012 · 17,288 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 · 7,360 accessesView PDFCite