Showing 141 - 160 results of 209 for search 'genetic algorithm ((optimizer OR optimized) OR optimize)', query time: 0.09s Refine Results
  1. 141

    Simultaneous stabilization of multimachine power systems viagenetic algorithms by Abdel-Magid, Y.L.

    Published 1999
    “…The problem of selecting the parameters of power system stabilizers which simultaneously stabilize this set of plants is converted to a simple optimization problem which is solved by a genetic algorithm with an eigenvalue-based objective function. …”
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  2. 142

    Computational Experience On Four Algorithms For The Hard Clustering Problem by AlSultan, K.S.

    Published 2020
    “…Several algorithms have been developed to solve this problem which include the k-means algorithm, the simulated annealing algorithm, the tabu search algorithm, and the genetic algorithm. …”
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    article
  3. 143

    Evolutionary algorithms for VLSI multi-objective netlist partitioning by Sait, Sadiq M.

    Published 2006
    “…In this paper, we engineer three iterative heuristics for the optimization of VLSI netlist bi-partitioning. These heuristics are based on Genetic Algorithms (GAs), Tabu Search (TS) and Simulated Evolution (SimE). …”
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  4. 144

    Experimental Investigation and Comparative Evaluation of Standard Level Shifted Multi-Carrier Modulation Schemes With a Constraint GA Based SHE Techniques for a Seven-Level PUC Inv... by Atif Iqbal (5504636)

    Published 2019
    “…Different standard multicarrier sinusoidal pulse-width modulation techniques (SPWMs) are adapted for the generation of switching gate signals for the PUC power switches, and these SPWMs are compared with novel optimization-based selective harmonic elimination (SHE) that employs genetic algorithm (GA) for solving nonlinear SHE equation with a constraint that eliminated all third-order harmonics efficiently. …”
  5. 145

    An evolutionary algorithm for solving the geometrically constrained site layout problem by Zouein, P.

    Published 2017
    “…The proposed algorithm is two-phases: an initialization phase that generates an initial population of layouts through a sequence of mutation operations, and a reproduction phase that evolve the layouts generated in phase one through a sequence of genetic operations aiming at finding an optimal layout. …”
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  6. 146

    Evolutionary algorithms, simulated annealing and tabu search: a comparative study by Youssef, H.

    Published 2020
    “…All rights reserved. Keywords: Genetic algorithms; Simulated annealing; Tabu search; Fuzzy logic; Floorplanning; Combinatorial optimization; VLSI…”
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    article
  7. 147

    A new multiobjective evolutionary algorithm forenvironmental/economic power dispatch by Abido, A.A.

    Published 2001
    “…A new nondominated sorting genetic algorithm (NSGA) based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and noncommensurable objectives. …”
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  8. 148

    Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study by Abido, M.A.

    Published 2003
    “…A comparative study of newly developed Pareto-based multiobjective evolutionary algorithms (MOEA) applied to a nonlinear power system multiobjective optimization problem is presented in this paper. …”
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    article
  9. 149

    Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

    Published 2025
    “…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …”
  10. 150

    Shape and sizing optimisation of space truss structures using a new cooperative coevolutionary-based algorithm by Dehkordi, Amin Abdollahi

    Published 2024
    “…This novel alternative optimisation strategy (CCMPA-GS) compared with 13 established genetic, evolutionary, swarm, and memetic meta-heuristic optimisation algorithms. …”
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  11. 151

    Cost-Benefit Analysis of Genotype-Guided Interruption Days in Warfarin Pre-Procedural Management by Islam, Eljilany

    Published 2022
    “…As per 10.3% prevalence of genetic variants, 82% bridging, and a calculated 20% optimization in the preparative period of warfarin management, the benefit to cost ratio was 4.0 in favor genotype-guided approach. …”
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  12. 152

    A hybrid of clustering and meta-heuristic algorithms to solve a p-mobile hub location–allocation problem with the depreciation cost of hub facilities by Mahdi Mokhtarzadeh (11593310)

    Published 2021
    “…To solve the proposed model, four meta-heuristic algorithms, namely multi-objective particle swarm optimization (MOPSO), a non-dominated sorting genetic algorithm (NSGA-II), a hybrid of k-medoids as a famous clustering algorithm and NSGA-II (KNSGA-II), and a hybrid of K-medoids and MOPSO (KMOPSO) are implemented. …”
  13. 153

    A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti (21593819)

    Published 2025
    “…This study focuses on optimizing and comparing various machine learning models for ASD diagnosis, while incorporating explainable AI techniques to ensure model transparency and interpretability. …”
  14. 154

    Implementation of a Multivariable Modular Structure for Fuzzy Taxi Scheduling System (FTSS) by Kouatli, Issam

    Published 2014
    “…Fuzzy logic can be utilized to deal with such uncertainty in the information. Genetic algorithm can be utilized for optimization of solution. …”
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  15. 155

    Performance driven standard-cell placement using the geneticalgorithm by Youssef, H.

    Published 1995
    “…In this paper we present a timing-driven placer for standard-cell IC design. The placement algorithm follows the genetic paradigm. Besides optimizing for area and wire length, the placer minimizes the propagation delays on a predicted set of critical paths. …”
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  16. 156

    Development and Implementation of a Hybrid Intelligent Controller for Interior Permanent Magnet Synchronous Motor Drives by Nasir Uddin, M.

    Published 2004
    “…At each operating condition a genetic algorithm is used to optimize the PI controller parameters in a closed-loop vector control scheme. …”
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    article
  17. 157

    A Novel Centrality-Based Approach for Link Prediction by El Khoury, Elissa Lichaa

    Published 2025
    “…Namely, we consider weighted betweenness, closeness and Katz centralities, in addition to the Resource Allocation and Adamic-Adar indices. We also use a genetic algorithm to optimize the weights of these metrics, reflecting their contributions to link prediction. …”
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  18. 158

    A new fuzzy logic controller based IPM synchronous motor drive by Abido, M.A.

    Published 2003
    “…The FLC parameters are optimized by genetic algorithm. The complete vector control scheme incorporating the FLC is successfully implemented in real-time using a digital signal processor board DS 1102 for a laboratory 1 hp interior permanent magnet (IPM) motor. …”
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  19. 159

    Parameterization and compensation of friction forces using geneticalgorithms by Al-Duwaish, H.N.

    Published 1999
    “…A PI controller with parameters optimized using genetic algorithms is used to control the position of a DC motor with friction. …”
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  20. 160

    Power system output feedback stabilizer design via geneticalgorithms by Abdel-Magid, Y.L.

    Published 1997
    “…In the second method, the problem of selecting the output feedback gains is converted to a simple optimization problem with an eigenvalue based objective function, which is solved by a genetic algorithm. …”
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