Search Results - (( rendering optimization system algorithm ) OR ( java application learning algorithm ))
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Hybrid scheduling and dual queue scheduling
Published 2009“…Our research work involves the design and development of new CPU scheduling algorithms (the Hybrid Scheduling Algorithm and the Dual Queue Scheduling Algorithm) with a view to optimization. …”
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Dynamic Economic Dispatch For Large Scale Power Systems: A Lagrangian Relaxation Approach
Published 1991“…Otherwise, Dantzig-Wolfe decomposition is invoked, using almost all the information generated during subgradient optimization to ensure a speedy conclusion. The computational efficiency of the algorithm renders it suitable for on-line dispatch.…”
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Hybrid scheduling and dual queue scheduling
Published 2009“…Our research work involves the design and development of new CPU scheduling algorithms (the Hybrid Scheduling Algorithm and the Dual Queue Scheduling Algorithm) with a view to optimization. …”
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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The advancement of artificial intelligence's application in hybrid solar and wind power plant optimization: a study of the literature
Published 2024“…Furthermore, this inquiry delves into the optimization strategies of these systems leveraging artificial intelligence methodologies. …”
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Development of intelligent evaluation system for product end-of-life selection strategy
Published 2011“…This study integrates the travelling salesman problem with genetic algorithm (TSP-GA) for finding the optimal disassembly sequence and disassembling the EOL product. …”
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Performance of 2-DOF PID controller in AGC of two area interconnected power system using PSO algorithm
Published 2022“…Therefore, in this work, particle swarm optimization (PSO) algorithm is formulated for tuning the gain values of the suggested controllers in multi-area interconnected system. …”
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Success history moth flow optimization for multi-goal generation dispatching with nonlinear cost functions
Published 2023“…The valve-point loading causes oscillations in the input-output characteristics of generating units, hence rendering the CEED problem an imperfect optimization problem. …”
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Integration of simulation for ergonomics assessment in operation control centre (railway industries) / Adib Zulfadhli Mohd Alias
Published 2019“…This study will focus on the translation of the CAD/Revit model into simulation software, either directly or through the intermediate stage of rendering package. Complete CAD/Revit model can be used to generate simulation model by straight forward translation of the whole model or with the algorithms for optimization. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…These methods present an effective alternative that treats plants as black-box systems without requiring explicit models. The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…These methods present an effective alternative that treats plants as black-box systems without requiring explicit models. The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Evaluating the Efficacy of Intelligent Methods for Maximum Power Point Tracking in Wind Energy Harvesting Systems
Published 2024“…However, the output power of a wind turbine is affected by various factors, such as wind speed, wind direction, and generator design. In order to optimize the performance of a WEHS, it is important to track the maximum power point (MPP) of the system. …”
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Fairness Categorization Policy Of Queuing Theory For Geographic Information System Job Scheduling
Published 2013“…Geographic Information System (GIS) is a compute-intensive plus data-intensive application that deals with substantial amount of spatial data processing and rendering of three-dimensional (3D) images of the locations. …”
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Development Of Machine Learning User Interface For Pump Diagnostics
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Intelligent traffic lights using Q-learning
Published 2022“…The Q-learning algorithm has been applied to the traffic lights system in this study. …”
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