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finding » findings (Expand Search)
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101
Efficient methods and techniques for the open-shop scheduling problem. (c2006)
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masterThesis -
102
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A time-domain algorithm for the analysis of second-harmonicgeneration in nonlinear optical structures
Published 2000“…A time-domain simulator of integrated optical structures containing second-order nonlinearities is presented. The simulation algorithm is based on nonlinear wave equations representing the propagating fields and is solved using the finite-difference time-domain method. …”
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A time-domain algorithm for the analysis of second-harmonicgeneration in nonlinear optical structures
Published 2000“…A time-domain simulator of integrated optical structures containing second-order nonlinearities is presented. The simulation algorithm is based on nonlinear wave equations representing the propagating fields and is solved using the finite-difference time-domain method. …”
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A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai
Published 2024“…The proposed framework comprises key elements: Important Decisions derived from interviews with transportation leaders, Knowledge Management enhanced by AI algorithms, Data Mining/Analysis utilizing historical data, the Fleet Management System employing Oracle ERP, and a Data-Driven Decision Support Framework that leans towards the extended framework approach. …”
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108
Genetic Algorithm Analysis using the Graph Coloring Method for Solving the University Timetable Problem
Published 2018“…Genetic algorithms were successfully useful to solve many optimization problems including the university Timetable Problem. …”
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109
GIJA:Enhanced geyser‐inspired Jaya algorithm for task scheduling optimization in cloud computing
Published 2024“…The motivation for this research stems from the increasing demand for efficient resource utilization and task management in cloud computing, driven by the proliferation of Internet of Things (IoT) devices and the growing reliance on cloud‐based services. Traditional task scheduling algorithms often face challenges in handling dynamic workloads, heterogeneous resources, and varying performance objectives, necessitating innovative optimization techniques. …”
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111
Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications
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doctoralThesis -
112
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113
Optimization of PV Cleaning Practices: Comparison Between Performance-Based and Periodic-Based Approaches
Published 2020“…It is important to choose the right cleaning strategy (method and frequency) to maximize the electricity production and economic performance of the PV facility. An optimization algorithm was developed and tested for multiple PV panel configurations based in Dubai Water and Electricity Authority’s (DEWA) outdoor test facil ity (OTF) solar lab. …”
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114
Predicting insulin dosage for diabetic patients to reach optimal glucose levels. (c2012)
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masterThesis -
115
Stochastic Programming for Hub Energy Management Considering Uncertainty Using Two-Point Estimate Method and Optimization Algorithm
Published 2023“…The proposed IARO-based scheduling framework’s performance is evaluated against that of traditional ARO, particle swarm optimization (PSO), and salp swarm algorithm (SSA). …”
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Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network
Published 2024“…Computational techniques, like the finite element method, are used to analyse behaviours based on varied input parameters. …”
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Logistics Optimization Using Hybrid Genetic Algorithm (HGA): A Solution to the Vehicle Routing Problem With Time Windows (VRPTW)
Published 2024“…The results showcase the outstanding performance of HGA, achieving Best-Known Solutions (BKS) for 11 instances and enhancing BKS solutions in one instance. Experimental findings validate that HGA-SIH consistently delivers results on par with or surpasses those obtained by several cutting-edge algorithms when evaluated based on various solution quality metrics. …”
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Bird’s Eye View feature selection for high-dimensional data
Published 2023“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
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Gradient-Based Optimizer (GBO): A Review, Theory, Variants, and Applications
Published 2023“…The review paper will be helpful for the researchers and practitioners of GBO belonging to a wide range of audiences from the domains of optimization, engineering, medical, data mining and clustering. As well, it is wealthy in research on health, environment and public safety. …”
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