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25 results for “Recurrent Neural Networks”
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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 PDFCite
Research ArticleOpen accessIn the abstractPreventing Deforestation in the Indian Landscape Through Neural Network-Based Intelligence Using Sound Event Detection and Advanced Feature Extraction TechniquesSallauddin Mohmmad, Suresh Kumar SanampudiForests play a vital role in maintaining ecological balance, regulating the climate, and conserving biodiversity. However, India’s forest landscape has witnessed significant changes between 1980 and 2024 due to deforestation, afforestation, and evolving conservation strategies. To address the challenges associated with forest monitoring, we proposed a model based on Sound Event Detection using a dataset comprising four classes: chainsaw sounds, … …Journal of Computer Science, Vol. 21, Issue 12 · 20 Jan 2026 · 1,899 accessesView PDFCite
Research ArticleOpen accessIn the abstractStock Closing Price Forecasting Using LSTM, Sentiment Analysis, Kalman FilterAssel Abdildayeva, Galymzhan Nurtugan, Guldana Taganova, Ardak AkhmetovaThe article explores the problem of predicting the closing prices of stocks using an innovative approach that combines methods of machine learning, sentiment analysis and noise filtering. The focus is on the development and testing of a comprehensive model that integrates recurrent neural networks (LSTM) for time series analysis, the GPT-3 language model for processing and analyzing textual data from … …Journal of Computer Science, Vol. 20, Issue 11 · 4 Sep 2024 · 6,262 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Deep Ensemble Framework for DDoS Attack Recognition and Mitigation in Cloud SDN EnvironmentS. Annie Christila, R. SivakumarMuch research has been done in the recent past on the absolute shift of Internet infrastructure in order to make it more significantly programmable, configurable and make it more conveniently feasible. Software Defined Networking (SDN) forms the basis for this absolute shift in Internet infrastructure. When you look at the benefits of an SDN-based cloud environment they are monumental. Namely, … …Journal of Computer Science, Vol. 20, Issue 10 · 5 Aug 2024 · 5,337 accessesView PDFCite
Research ArticleOpen accessIn the abstractA CNN-KNN Based Recognition of Online Handwritten Symbols within Physics Expressions Using Contour-Based Bounding Box (CBBS) Segmentation TechniqueUjwala Kolte, Sachin Naik, Vidya KumbharArtieres, T., Marukatat, S., & Gallinari, P. (2007). Online Handwritten Shape Recognition Using Segmental Hidden Markov Models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(2), 205–217. https://doi.org/10.1109/tpami.2007.38 Baró, A., Riba, P., Calvo-Zaragoza, J., & Fornés, A. (2019). From Optical Music Recognition to Handwritten Music Recognition: A baseline. Pattern Recognition Letters, 123, 1–8. https://doi.org/10.1016/j.patrec.2019.02.029 Bresler, M., Prua, D., & Hlavác, … …Journal of Computer Science, Vol. 20, Issue 7 · 7 May 2024 · 6,278 accessesView PDFCite
Research ArticleOpen accessIn the abstractRoute Optimization using Hybrid GRU Learning Model for SDN and Edge-Based VANET TopologySavitha Kumar, Chandrasekar ChinnasamyIntelligent Transportation System (ITS) offersoutstanding features, including security applications and emergency alerts.Unfortunately, ITS limits traffic control services, adaptability, andadjustability due to the traffic volume. Hence, expanding the standard VehicularAd hoc Networks (VANET) framework is a requirement. As a result, in the latestdays, the concept of Software-Defined Networking based Vehicular Ad hocNetworks (SDN-VANETs) has drawn considerable attention, creating VANETssmarter. The SDN-VANETs … …Journal of Computer Science, Vol. 18, Issue 8 · 26 Aug 2022 · 6,160 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of Deep Learning Models for Multi-Step Prediction of Financial Time SeriesSaugat Aryal, Dheynoshan Nadarajah, Prabath Lakmal Rupasinghe et al.Financial time series prediction has been a key topic of interest among researchers considering the complexity of the domain and also due to its significant impact on a wide range of applications. In contrast to one-step ahead prediction, multi-step forecasting is more desirable in the industry but the task is more challenging. In recent days, advancement in deep learning has … …Journal of Computer Science, Vol. 16, Issue 10 · 27 Oct 2020 · 6,967 accessesView PDFCite
Research ArticleOpen accessIn the abstractPrediction of Data Traffic in Telecom Networks based on Deep Neural NetworksQuang Hung Do, Thi Thanh Hang Doan, Thi Van Anh Nguyen et al.Accurate prediction of data traffic in telecom network is a challenging task for a better network management. It advances dynamic resource allocation and power management. This study employs deep neural networks including Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) techniques to one-hour-ahead forecast the volume of expected traffic and compares this approach to other methods including Adaptive Neuro-Fuzzy … …Journal of Computer Science, Vol. 16, Issue 9 · 30 Sep 2020 · 8,059 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Evaluation of Deep Learning Networks on Printed Odia CharactersSanjibani Sudha Pattanayak, Sateesh Kumar Pradhan, Ramesh Chandra MalikDeep machine learning includes a series of layers to mimic the working of the human brain for taking a decision. Deep learning networks have shown good results in character recognition in the past. This paper evaluates the performance of different deep learning networks like Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) based recurrent neural network and Convolutional LSTM on … …Journal of Computer Science, Vol. 16, Issue 7 · 25 Jul 2020 · 6,785 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetection of Respiratory Abnormalities Using Artificial Neural NetworksMahdi J. Baemani, Amirhasan Monadjemi, Payman MoallemProblem Statement: Lung disease is a major threat to the human health regarding the industrial life, air pollution, smoking, and infections. Lung function tests are often performed using spirometry. Approach: The present study aims at detecting obstructive and restrictive pulmonary abnormalities. Lung function tests are often performed using spirometry. In this study, the data were obtained from 250 volunteers with … …Journal of Computer Science, Vol. 4, Issue 8 · 31 Aug 2008 · 6,634 accessesView PDFCite