78 results for “AI-Based Forecasting”

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Research ArticleOpen accessEvery word in the titleDesign 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 · 7,627 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titleForecasting Air Temperatures Using Time Series Models and Neural-based AlgorithmsMahmoud M. Smadi, Farouq S. MjalliRecently, neural network models have been popular and found useful for forecasting a wide variety of time series data in many disciplines. This is due to their favorable modeling properties of simplicity, fault and noise tolerance and their capability to adapt to process changes. Nevertheless, applications in climatology have been less widespread than other disciplines such as economics. In this … …Journal of Mathematics and Statistics, Vol. 3, Issue 2 · 30 Jun 2007 · 7,272 accessesView PDF Cite

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 · 7,792 accessesView PDF Cite

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 · 7,268 accessesView PDF Cite

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 PDF Cite

Research ArticleOpen accessIn the abstractImplementing a Hybrid VMD–BiTCN–BiGRU Architecture With Intelligent Optimization for Agricultural Commodity Price Prognostication in Gujarat MarketsJignesh Hirapara, Ratnesh Kumar Namdeo, Ankit Kumar Dubey et al.In the agricultural sector, the prices of pulses require adequate forecasting to plan farming activities, store and market, and guide policy-making. However, the pulse price series is highly volatile, seasonal, nonstationary, and nonlinear, and thus conventional linear time series models are not necessarily very effective. In the suggested framework, the raw price data series is decomposed using Variational Mode Decomposition … …Journal of Computer Science, Vol. 22, Issue 7 · 1 Aug 2026 · 1,021 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA Sentiment Analysis Approach for Affective State Recognition With SWISH-Activated DenseNet-169 in Human Event ForecastingKarthik Elangovan, Prabhakaran Paulraj, Dinesh Babu G L et al.Detecting human feelings from images is perhaps one of the most useful and challenging social communication problems in research. Emotion detection-based deep computing outperforms classic image processing techniques. Facial recognition technology has permeated every aspect of our daily lives, from unlocking our phones to getting private file access on our systems. Machine Learning and Deep Learning make it easy to … …Journal of Computer Science, Vol. 22, Issue 8 · 29 Jul 2026 · 1,211 accessesView PDF Cite

Research ArticleOpen accessIn the abstractDeep Learning Models for Predicting Stock Closing Prices in the Saudi Stock MarketAreej Alhumaidi, Hoda A. AbdelhafezFinancial time series data are inherently volatile and nonlinear, presenting considerable challenges in accurately forecasting stock market trends. This study aims to predict the closing prices of companies listed on the Saudi stock market by analyzing historical data spanning from 2013 to 2023. To this end, four deep learning models were employed-Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), Gated Recurrent … …Journal of Computer Science, Vol. 22, Issue 4 · 22 Apr 2026 · 1,355 accessesView PDF Cite

Research ArticleOpen accessIn the abstractConvergence of GenAI and RPA: A Digital Heaven in Supply Chain Optimization ProcessSaurabh A. Pahune, Zahid Akhtar, Manoj Chandrasekharan et al.One of the most groundbreaking advances in the field of intelligent automation is the merging of Generative Artificial Intelligence (GenAI) and Robotic Process Automation (RPA). This combination unlocks previously unachievable capabilities in automation. RPA (software bots) improves speed and operational efficiency by automating rule-based tasks, Standard Operating Procedures (SOPs), and repetitive workflows. At the same time, it minimizes manual labor … …Journal of Computer Science, Vol. 21, Issue 12 · 8 Feb 2026 · 2,040 accessesView PDF Cite

Research ArticleOpen accessIn the abstractPredictive Analytics and Procurement Visibility: A Big-Data-Driven Approach to Customer Satisfaction in Supply Chain ManagementDevendra Nath Pathak, Rakesh Kumar Yadav, Hitendra SinghIn the current dynamic and consumer driven market environment, supply chains need to move out of reactive to the proactive ecosystems. One of the most urgent requirements is increasing procurement visibility and the development of better order planning for the inventory to meet the products’ demand with continued high customer satisfaction. This paper is an agenda of big-data-driven predictive analytics … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 2,442 accessesView PDF Cite