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81 results for “Forecasting Models”
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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 · 1,626 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleModelling and Forecasting Volatility of Returns on the Ghana Stock Exchange Using Garch ModelsFrimpong Joseph Magnus, Oteng-Abayie Eric FosuThis paper models and forecasts volatility (conditional variance) on the Ghana Stock Exchange using a random walk (RW), GARCH(1,1), EGARCH(1,1), and TGARCH(1,1) models. The unique ‘three days a week’ Databank Stock Index (DSI) was used to study the dynamics of the Ghana stock market volatility over a 10-year period. The competing volatility models were estimated and their specification and forecast … …American Journal of Applied Sciences, Vol. 3, Issue 10 · 31 Oct 2006 · 7,551 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAI-Integrated Probabilistic Optimization for Inventory Control Under Stochastic DemandJanardan BeheraThe identification and operationalization of increasingly nonstationary and volatile demand patterns challenge the conduct of inventory management in contemporary supply chains. The classical models, especially EOQ and static policies, rest on the stability of demand assumptions, either deterministically or distributionally, and are hence less apt under real-world uncertainty. In view of these limitations, the present study puts forward an integrated … …Journal of Mathematics and Statistics, Vol. 22, Issue 1 · 6 May 2026 · 2,217 accessesView PDFCite
Review ArticleOpen accessIn the keywordsDecoding Late Blight of Potato and Tomato: Insights into Pathogen Dynamics, Host Interactions and Emerging SolutionsHumayra Ferdus, Mahabuba Mostafa, Dodi Al Sharif, Md. Motaher HossainThe oomycete Phytophthora infestans is the source of late blight, a devastating disease that significantly impacts on tomato and potato cultivation worldwide, threatening food security and causing considerable economic losses. This review explores the epidemiological dynamics of late blight, focusing on the pathogen's life cycle, reproductive strategies, and molecular pathogenesis. Traditional management strategies, including cultural practices, host resistance, and biocontrol … …OnLine Journal of Biological Sciences, Vol. 25, Issue 4 · 5 Feb 2026 · 2,530 accessesView PDFCite
Research ArticleOpen accessIn the keywordsForecasting the Stock Exchange of Thailand uses Day of the Week Effect and Markov Regime Switching GARCHP. Sattayatham, N. Sopipan, B. PremanodeProblem statement: We forecast return and volatility of the Stock Exchange of Thailand (SET) Index. Approach: In this study, we modeled the SET Index returns using mean equation with day of the week effect and autoregressive moving-average. Next we forecast the volatility of the SET Index by using the GARCH-type model and the Markov Regime Switching GARCH (MRS-GARCH) model. Results: … …American Journal of Economics and Business Administration, Vol. 4, Issue 1 · 15 Mar 2012 · 7,865 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFuzzy Time Series: An Application to Tourism Demand ForecastingMuhammad Hisyam Lee, Maria Elena Nor, Suhartono et al.Problem statement: Forecasting is very important in many types of organizations since predictions of future events must be incorporated into the decision-making process. In the case of tourism demand, better forecast would help directors and investors make operational, tactical and strategic decisions. Besides that, government bodies need accurate tourism demand forecasts to plan required tourism infrastructures, such as accommodation site … …American Journal of Applied Sciences, Vol. 9, Issue 1 · 24 Nov 2011 · 8,474 accessesView PDFCite
Research ArticleOpen accessIn the keywordsShort-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 keywordsFORECASTING RETURNS FOR THE STOCK EXCHANGE OF THAILAND INDEX USING MULTIPLE REGRESSION BASED ON PRINCIPAL COMPONENT ANALYSISNop Sopipan, Anchalee Sattayatham, Samruam ChongcharoenThe aim of this study was to forecast the returns for the Stock Exchange of Thailand (SET) Index by adding some explanatory variables and stationary Autoregressive Moving-Average order p and q (ARMA (p, q)) in the mean equation of returns. In addition, we used Principal Component Analysis (PCA) to remove possible complications caused by multicollinearity. Afterwards, we forecast the volatility … …Journal of Mathematics and Statistics, Vol. 9, Issue 1 · 18 Mar 2013 · 7,438 accessesView PDFCite
Research ArticleOpen accessIn the keywordsForecasting 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 abstractDynamic Knowledge Driven Multi-Scale Spatiotemporal Fusion Framework for Reliable Multi-Horizon Traffic Flow ForecastingDeepika M S, P. Deepa Shenoy, Venugopal K RAccurate traffic flow forecasting remains a core challenge in intelligent transportation systems. Urban traffic patterns are characterised by complex spatiotemporal dependencies and inherent uncertainties, which complicate traffic forecasting. This study proposes a Dynamic Knowledge-Driven Spatiotemporal Fusion (DKDMSF) architecture to extract features of Multi-Scale traffic dynamics across various temporal traffic horizons. DKDMSF integrates Dynamic Spatial Attention (DSA) and Adaptive Graph Learning … …Journal of Computer Science, Vol. 22, Issue 9 · 30 Sep 2026 · 413 accessesView PDFCite