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53 articles for “Hybrid Architecture”
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Research ArticleOpen accessIn the abstractA 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 · 6,675 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Systematic Review of Artificial Intelligence and Deep Learning Approaches for Cocoa Pod Disease DetectionHenry Techie-Menson, Michael Asante, Yaw Marfo Missah et al.Cocoa pod diseases destroy an estimated 700,000 metric tons of cocoa annually, threatening 40–50 million smallholder farmers across tropical regions. Accurate field diagnosis remains constrained by symptom similarity, labour-intensive scouting, and limited specialist access in remote communities. This paper presents a PRISMA-guided systematic review of 25 peer-reviewed studies on automated cocoa pod disease detection and classification (2016–2026), addressing architectural approaches, … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Sep 2026 · 743 accessesView PDFCite
Research ArticleOpen accessIn the abstractUzNER: A Human-Reviewed Benchmark for Uzbek Named Entity Recognition With Gazetteer-Augmented Transformer ModelsBobur Saidov, Vladimir Barakhnin et al.UzNER-100K is a large-scale human-reviewed benchmark for Uzbek named entity recognition with 100,000 training sentences, 18 fine-grained entity types and 200,083 entity mentions across 114,269 sentences in total. The corpus was constructed through an LLM-assisted, expert-reviewed annotation pipeline that achieved strong reliability on the main audit subset while substantially reducing corpus-construction effort. The benchmark includes a standard test split, a … …Journal of Computer Science, Vol. 22, Issue 6 · 22 Jun 2026 · 1,318 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comprehensive Review of Medical Image Denoising: Techniques, Challenges, Applications and Future DirectionsMohit Sharma, Ayush Dogra, Anita Gupta et al.The concept of noise reduction in medical images plays a vital role in improving image quality and accuracy associated with diagnosis, and facilitating reliable automated analysis. This survey presents a structured overview of medical image denoising, beginning with foundational definitions and noise models for modalities such as MRI and CT. We critically evaluate persistent gaps, including the limited generalizability of … …Journal of Computer Science, Vol. 22, Issue 3 · 28 Mar 2026 · 1,861 accessesView PDFCite
Research ArticleOpen accessIn the abstractSystematic Literature Review of Graph Neural Networks in Disaster Management: Methods, Applications, and Future DirectionsSularno, Wendi Boy, Putri Anggraini et al.The increasing frequency and complexity of natural disasters underscore the urgent need for intelligent systems that support timely and effective decision-making. Graph Neural Networks (GNNs) have emerged as a powerful deep-learning paradigm for modeling spatial and relational data, offering distinct advantages for disaster management. This study presents a Systematic Literature Review (SLR) of GNN-based approaches for disaster mitigation, emergency response, … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 2,043 accessesView PDFCite
Research ArticleOpen accessIn the abstractSelf-Supervised Contrastive Learning for Steering Angle Prediction in Autonomous Driving SimulationsMaxson Phang, Suryadiputra LiawatimenaPredicting steering angles is a crucial task in autonomous driving, with end-to-end deep learning being a widely used approach. However, such models often suffer from overfitting to learned trajectories, limiting their generalization to new data. To address this, self-supervised contrastive learning is explored as an alternative, allowing models to learn meaningful representations without labeled data. The primary objective is to … …Journal of Computer Science, Vol. 21, Issue 9 · 20 Oct 2025 · 2,588 accessesView PDFCite
Research ArticleOpen accessIn the abstractPRESERVATION OF THE PRIVACY FOR MULTIPLE CUSTODIAN SYSTEMS WITH RULE SHARINGB. Murugeshwari, C. Jaya Kumar, K. SarukesiThe aim of the research work is to mine the data set available with each custodian in a semi honest model, securely without disclosure of any data amongst various custodians involved. No custodian discloses any information. In the proposed scheme in order to reduce the computational complexity, the data partitioning has been done in the horizontal way. The proposed research … …Journal of Computer Science, Vol. 9, Issue 9 · 6 Aug 2013 · 6,314 accessesView PDFCite
Research ArticleOpen accessIn the abstractNovel Adaptive Job Scheduling Algorithm on Heterogeneous Grid ResourcesG. K. Kamalam, V. Murali BhaskaranGrid provides an infrastructure for sharing geographically distributed heterogeneous resources to process many applications and mainly used for solving scientific problems that requires more computation time. Problem statement: Grid is a dynamic environment, where the resources may join or leave the environment at any time and the jobs also arrives at different intervals of time. To meet the demands and … …American Journal of Applied Sciences, Vol. 9, Issue 8 · 6 Jul 2012 · 6,853 accessesView PDFCite
Research ArticleOpen accessIn the abstractEVALUATION OF HIDDEN MARKOV MODEL BASED ADAPTIVE PROVISIONING OF OPTICAL BURST SWITCHING NETWORKS AMENABLE FOR UPGRADATION TO GREEN FLEXIGRID NETWORKSP. G.V. Ramesh, Prita NairCatering to the evolving bandwidth-on-demand applications requires flexible provisioning architectures that ensure fairness to both high end and low end users of internet. Dynamic classification of network paths into long and short, based on traffic dependent connection holding times and a wavelength allocation from different subsets for these categories is a necessity for implementing energy saving hybrid switching, loss recovery … …Journal of Computer Science, Vol. 10, Issue 5 · 16 Jan 2014 · 6,522 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA Context Aware Deep Learning Framework for Multi-Level Arabic Fake News Detection Using Hybrid Linguistic RepresentationsNoor Mahmoud Alkudah, Somia Abufakher, Raja Masadeh et al.The rapid spread of false information on social media has made it even more important to be able to spot false news, especially in Arabic-speaking areas where language is more complicated and news is organized in a hierarchy. Recent research show that deep learning and transformer-based models work well, but most of them only look at performance metrics and don't … …Journal of Computer Science, Vol. 22, Issue 3 · 27 Mar 2026 · 1,577 accessesView PDFCite