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  1. 201

    Virtual Inertia Support in Power Systems for High Penetration of Renewables—Overview of Categorization, Comparison, and Evaluation of Control Techniques by Naruttam Kumar Roy (16904544)

    Published 2022
    “…Integrating intelligent methods, such as fuzzy logic, genetic algorithm, non-convex optimization, and heuristic optimization, signify intelligent control methods. …”
  2. 202

    AI-Augmented Metasurface Synthesis for Dynamic Beam Steering in Reconfigurable Antenna Arrays by Bostani, Ali

    Published 2025
    “…As compared to the conventional heuristic methods, for example, genetic algorithms (GA), particle swarm optimization (PSO), the approach based on DRLs has rapid policy convergence, has relatively less computational latency, and is autonomous to adapt to dynamic wireless conditions. …”
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  3. 203

    Hybridizing rule-based power system stabilizers with geneticalgorithms by Abido, M.A.

    Published 1999
    “…The proposed approach uses genetic algorithms (GA) to search for optimal settings of rule-based power system stabilizer (RBPSS) parameters. …”
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  4. 204

    Application of Metastructures for Targeted Low-Frequency Vibration Suppression in Plates by Ratiba F. Ghachi (14152455)

    Published 2022
    “…<h2>Purpose</h2> <p>We present an approach that combines finite element analysis and genetic algorithms to find the optimal configuration of local resonators created in the host structure to suppress their vibration in a target low-frequency range. …”
  5. 205

    Tuning of a fuzzy logic power system stabilizer using geneticalgorithms by Abido, M.A.

    Published 1997
    “…The proposed approach uses genetic algorithms (GA) to search for optimal or near optimal settings of fuzzy logic power system stabilizer (FLPSS) parameters. …”
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  6. 206

    AI-Based Methods for Predicting Required Insulin Doses for Diabetic Patients by Azar, Danielle

    Published 2015
    “…In this paper, we propose and compare three techniques two of which are Artificial Intelligence techniques, namely C4.5 and Case-Based Reasoning, and the third one is a meta-heuristic namely genetic algorithms. The performance of the three algorithms is evaluated on a data set found in the public UCMI repository.…”
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  7. 207

    General iterative heuristics for VLSI multiobjective partitioning by Sait, Sadiq M.

    Published 2003
    “…In this paper, we engineer two iterative heuristics for the optimization of VLSI netlist bi-Partitioning. These heuristics are based on Genetic Algorithms (GAs) and Tabu Search (TS) and incorporate fuzzy rules in order to handle the multiobjective cost function. …”
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  8. 208

    An Evolutionary Meta-Heuristic for State Justification in Sequential Automatic Test Pattern Generation by El-Maleh, Aiman H.

    Published 2001
    “…Evolutionary algorithms have been effective in solving many search and optimization problems. …”
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  9. 209

    An evolutionary meta-heuristic for state justification insequential automatic test pattern generation by El-Maleh, A.H.

    Published 2001
    “…Evolutionary algorithms have been effective in solving many search and optimization problems. …”
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