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16 results for “self-optimization”
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Research ArticleOpen accessIn the keywordsPredictive Autonomicity of Web Services in the MAWeS FrameworkEmilio P. Mancini, Massimiliano Rak, Roberto Torella, Umberto VillanoIn Web Services designs classical optimization techniques are not applicable. A possible solution to guarantee critical requirements is the use of an autonomic architecture, able to auto-configure and to auto-tune. This study presents MAWeS (MetaPL/HeSSE Autonomic Web Services), a framework whose aim is to support the development of self-optimizing predictive autonomic systems for Web service architectures. It adopts a simulation-based … …Journal of Computer Science, Vol. 2, Issue 6 · 30 Jun 2006 · 7,067 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDeveloping and Testing Dynamic Models for HVAC Systems Using System Identification ApproachNabil Nassif, Jasmine Buford, Taher M. Abu-LebdehThis paper proposes integrated modeling and optimization methods for a chilled water HVAC system using a system identification approach. Two multiple input-single output models are developed to find the supply air temperature and fan power of the investigated chilled water air handling unit AHU. To test the proposed models, actual data are collected from existing HVAC systems. Different fan and … …American Journal of Engineering and Applied Sciences, Vol. 10, Issue 1 · 15 Mar 2017 · 7,710 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA New Three-Term Preconditioned Gradient memory Algorithm for Nonlinear Optimization ProblemsAbbas Y. AL-Bayati, Ivan S. LatifIn the present study, we proposed a three-term of preconditioned gradient memory algorithms to solve a nonlinear optimization problem. The new algorithm subsumes some other families of nonlinear preconditioned gradient memory algorithms as its subfamilies with Powell's Restart Criterion and inexact Armijo line searches. Numerical experiments on twenty one well-known test functions with various dimensions generally encouraged and showed that … …Journal of Mathematics and Statistics, Vol. 4, Issue 2 · 30 Jun 2008 · 6,781 accessesView PDFCite
Research ArticleOpen accessIn the abstractMulti-Agent Energy Allocation Optimization in Local Energy Communities: A Comparative StudyAmira Dhorbani, Dhaker Abbes, Benoît Robyns, Kahina Hassam OuariThe growing diversity of energy demands, combined with the integration of renewable and distributed energy systems, calls for more adaptive energy management strategies. This study presents a comparative simulation-based analysis of three energy management approaches applied to a local energy community: A Multi-Agent System (MAS), a centralized rule-based method, and a game-theory-based optimization using the Alternating Direction Method of Multipliers … …American Journal of Applied Sciences, Vol. 22, Issue 1 · 30 Dec 2025 · 3,381 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 · 2,581 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intelligent Approach to Develop, Assess and Optimize Energy Consumption Models for Air-Cooled Chillers using Machine Learning AlgorithmsMostafa Tahmasebi, Nabil NassifThe building sector accounts for more than 70% of the total electricity use. Chillers consume more than 50% of electrical energy during seasonal periods of building use. With the growth of the building sector and climate change, it's essential to develop energy-efficient HVAC systems that optimize the ever-increasing energy demand. This study aims to develop an energy consumption prediction model … …American Journal of Engineering and Applied Sciences, Vol. 15, Issue 3 · 8 Nov 2022 · 5,516 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Approaches for Early Detection of Skin Cancer Disease Detection Using Segmentation and Classification with Severity AnalysisPunam R. Patil, Ritu TandonThe utmost prevalent type of the disease, skin cancer claims millions of lives every year, poses a serious public health threat particularly melanoma, which is often fatal if not detected early. Early diagnosis is crucial, yet traditional methods frequently fall short due to image quality limitations and the complexity of visual differentiation. With an emphasis on severity analysis, this study … …Journal of Computer Science, Vol. 21, Issue 9 · 24 Nov 2025 · 2,051 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Antigenic Peptides Using a Multi-Level Transformer Model with Enhanced Feature SelectionAshwini S., Minu R. I., Jeevan KumarThis Antigenic Peptide (APs) prediction is one of the most important roles to improve vaccine design and interpret immune responses. This paper develops a Multi-Level Pooling-based Transformer model, which improves the accuracy and efficiency of predicting T-cell epitopes. The model utilizes peptide sequences from the Immune Epitope Database, employing a refined Kolaskar and Tongaonkar algorithm for feature extraction and a … …Journal of Computer Science, Vol. 21, Issue 7 · 17 Jul 2025 · 3,443 accessesView PDFCite
Research ArticleOpen accessIn the abstractMIGITATION OF INTER CELL INTERFERENCE AND FADING IN LTE SYSTEMSNagarajan Amutha Prabha, Gorla Vidhya Sagar, Venugopal ManikandanIn this study we investigate the compensation of outage area utmost. It introduces the self optimization of the neighbors of the outage cells with antenna tilts for the generation of the most suitable configuration settings for the network with base stations/eNodeBs positional information. All the neighbors of the outage cell increase their coverage area and thus contribute to cell outage … …Journal of Computer Science, Vol. 10, Issue 3 · 28 Nov 2013 · 6,736 accessesView PDFCite