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77 articles for “AI-Based Forecasting”
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Research ArticleOpen accessEvery word in the titleForecasting Peak Load Electricity Demand Using Statistics and Rule Based ApproachZ. Ismail, A. Yahya, K. A. MahpolProblem statement: Forecasting of electricity load demand is an essential activity and an important function in power system planning and development. It is a prerequisite to power system expansion planning as the world of electricity is dominated by substantial lead times between decision making and its implementation. The importance of demand forecasting needs to be emphasized at all level as … …American Journal of Applied Sciences, Vol. 6, Issue 8 · 31 Aug 2009 · 7,936 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEfficient Rainfall Forecasting Using Sequential Momentum-Based Artificial Neural Networks for Urban Flood ManagementSherin K K, G. SuganthiUrban floods cause severe disruption in densely populated cities and damage essential public infrastructure. Rapid urbanization and weak drainage systems further increase the risk during heavy rainfall. Accurate short-term rainfall forecasting is required to support early warning and reduce losses. This research focuses on improving rainfall prediction accuracy using an Artificial Neural Network trained with a new optimizer named Sequential … …Journal of Computer Science, Vol. 22, Issue 4 · 9 Apr 2026 · 1,539 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA NOVEL APPROACH BASED ON GENETIC FUZZY CLUSTERING AND ADAPTIVE NEURAL NETWORKS FOR SALES FORECASTINGAttariuas Hichama, Bouhorma Mohameda, El Fallahi AbdellahbThis article proposes a new hybrid sales forecasting system based on genetic fuzzy clustering and Back-Propagation (BP) Neural Networks with adaptive learning rate (GFCBPN).The proposed architecture consists of three stages: (1) utilizing Winter’s Exponential Smoothing method and Fuzzy C-Means clustering, all normalized data records will be categorized into k clusters; (2) using an adapted Genetic Fuzzy System (MCGFS), the fuzzy … …Journal of Computer Science, Vol. 9, Issue 8 · 2 Jul 2013 · 6,669 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleFORECASTING 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 accessEvery word in the titleA Hybrid Approach based on Winter's Model and Weighted Fuzzy Time Series for Forecasting Trend and Seasonal DataSuhartono, Muhammad Hisyam LeeProblem statement: In the literature, the most studied of fuzzy time series for the purpose of forecasting is the first order fuzzy time series model. In this model, only the first lagged variable is used when constructing the first order fuzzy time series model. Therefore, such approaches fail to analyze accurately trend and seasonal time series which is an important … …Journal of Mathematics and Statistics, Vol. 7, Issue 3 · 18 Jul 2011 · 7,942 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleConstructing Fuzzy Time Series Model Based on Fuzzy Clustering for a ForecastingAshraf K. Abd Elaal, Hesham A. Hefny, Ashraf H. Abd ElwahabProblem statement: In this study researchers introduced a fuzzy time series model depending on fuzzy clustering to solve the problem in which the membership values are assumed as Song and Chissom model and to increase the performance of fuzzy time series model. Approach: Proposed model employed seven main procedures in time-invariant fuzzy time-series and time-variant fuzzy time series models. In … …Journal of Computer Science, Vol. 6, Issue 7 · 31 Jul 2010 · 9,748 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleElectricity 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 · 8,274 accessesView PDFCite
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 titleA STUDY ON NEW PRODUCT DEMAND FORECASTING BASED ON BASS DIFFUSION MODELZuhaimy Ismail, Noratikah AbuA forecasting model of new product demand has been developed and applied to forecast new vehicle demand in Malaysia. Since the publication of the Bass model in 1969, innovation of new diffusion theory has sparked considerable research among marketing science scholars, operational researchers and mathematicians. This study considers the Bass Model for forecasting the diffusion of new products or an … …Journal of Mathematics and Statistics, Vol. 9, Issue 2 · 29 Apr 2013 · 7,807 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleFORECASTING THE FINANCIAL RETURNS FOR USING MULTIPLE REGRESSION BASED ON PRINCIPAL COMPONENT ANALYSISNop SopipanThe 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 order p (AR (p)) in the mean equation of returns. In addition, we used Principal Component Analysis (PCA) to remove possible complications caused by multicollinearity. Results showed that the multiple regressions based on PCA, … …Journal of Mathematics and Statistics, Vol. 9, Issue 1 · 17 Apr 2013 · 6,958 accessesView PDFCite