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163 results for “Forecasting”
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Research ArticleOpen accessEvery word in the titleEnhancing Dam Safety and Management: Long Short-Term Memory Based Predictive Models for Accurate Alert ForecastingNisha C. M, N. ThangarasuDam management and early alert systems are critical for effective water resource management. Accurate prediction of dam alert signals facilitates proactive decision-making, thereby aiding in the effective management and reduction of potential risks linked to dam operations. Within this research, Long Short-Term Memory (LSTM) networks are utilized to forecast dam alert signals issued from the dam by leveraging daily parameters, … …Journal of Computer Science, Vol. 22, Issue 1 · 6 Feb 2026 · 1,632 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEnhancing Electric Vehicle Charging Demand Prediction Using a Novel SAE-DNN Neural Network Model for Probabilistic ForecastingNaga Raju Hari Manikyam, A. Thangam, J. Murugachandravel et al.The rapid growth and widespread adoption of Electric Vehicles (EVs) play a crucial role in the progress of intelligent transportation systems, resulting in a significant decrease in environmentally damaging greenhouse gas emissions. The increase in EV usage has made it crucial to develop charging infrastructure to keep up with the growing demand. Precisely predicting EV charging demand is crucial to … …Journal of Computer Science, Vol. 21, Issue 10 · 11 Dec 2025 · 3,543 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleForecasting of Multistep Multivariate Financial Data Through GSO Algorithm Infused Vanilla LSTM ModelNikhitha Pai, Ilango Velchamy, Nithya B RameshPredicting time series in the financial domain requires using models that can do sequence processing tasks. One such model is the LSTM model which belongs to the family of deep learning networks. The performance measure of LSTM in a regression task is to bring down the error in the predicted values. In this study, a novel fused LSTM model integrating … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 6,077 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleForecasting the Diffuse Solar Radiation by using a New Modeling over Saudi ArabiaSamy A. KhalilWithin the arranging and execution assessment of solar energy projects, particularly within the planning and estimation of solar photovoltaic sources as elective energy sources within the future, exact evaluation of Diffuse Solar Radiation (DSR) is one of the essential and basic issues. The target of this article is to use the new model to predict DSR in four different locations … …American Journal of Applied Sciences, Vol. 18, Issue 1 · 5 May 2021 · 7,354 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleForecasting 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 · 8,607 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleModeling and Forecasting of International Tourism Demand in ASEAN CountriesAsrin Karimi, Pouya Faroughi, Khalid Abdul RahimThis study attempts to find the best model to forecast international tourism demand using a series of key macroeconomic variables in ASEAN countries. Generally, we find that generalized Poisson regression model is the best one for estimating long-run international tourism demand. In addition, we find that inflation and real exchange rate have negative relationship with international tourism demand. On the … …American Journal of Applied Sciences, Vol. 12, Issue 7 · 8 Aug 2015 · 7,944 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Hybridization of Enhanced Artificial Bee Colony-Least Squares Support Vector Machines for Price ForecastingZuriani Mustaffa, Yuhanis YusofProblem statement: As the performance of Least Squares Support Vector Machines (LSSVM) is highly rely on its value of regularization parameter, γ and kernel parameter, σ2, man-made approach is clearly not an appropriate solution since it may lead to blindness in certain extent. In addition, this technique is time consuming and unsystematic, which consequently affect the generalization performance of LSSVM. … …Journal of Computer Science, Vol. 8, Issue 10 · 28 Aug 2012 · 6,802 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleNeural Networks Based Nonlinear Time Series Regression for Water Level Forecasting of Dungun RiverSiti Hajar Arbain, Antoni WibowoThe Department of Irrigation and Drainage (DID) Malaysia and Meteorological Malaysia Department (MMD) has been measured the flood characteristics benchmark which included water level, area inundation, peak inundation, peak discharge, volume of flow and duration of flooding. In terms of water levels, DID have introduced three categories of critical level stages namely normal, alert and danger levels. One of the … …Journal of Computer Science, Vol. 8, Issue 9 · 13 Aug 2012 · 7,800 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleForecasting of Energy Consumption and Pollutant Emission for Road Transportation Policies EvaluationPunravee Kongboontiam, Rungsun UdomsriProblem statement: The energy demand in Thailand has significantly increased over last ten years, particularly in transportation sector. Road transportation contributes the highest energy consumption, 38% of the total energy in the whole country, but it consumes 60% of the total energy usage in the northern region of Thailand. Various chemical pollutants emitted from the road transportation affecting to human … …Energy Research Journal, Vol. 2, Issue 1 · 23 Jan 2012 · 7,722 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleArtificial Neural Network Based Model for Forecasting Sugar Cane ProductionO. O. Obe, D. K. ShangodoyinProblem statement: The global need for alternative energy source has necessitated the exploration of vast organic agricultural products with a view of processing them for the production of ethanol in commercial quantity. To ascertain a sustainable production of ethanol from processed sugar cane, a predictive model based on non-linearity nature of its production is imperative. This is due to unavailability … …Journal of Computer Science, Vol. 6, Issue 4 · 30 Apr 2010 · 7,272 accessesView PDFCite