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  1. 81

    Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function by Duffuaa, S. O.

    Published 2020
    “…A fuzzy relation between observed/input parameters and required/output characteristics is proposed. A genetic algorithm is developed to obtain optimal process targets. …”
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    article
  2. 82

    Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network by Mohammad Reza Chalak Qazani (13893261)

    Published 2024
    “…Additionally, the multi-objective genetic algorithm (MOGA) was utilised to extract the most optimal parameters for the injection moulding process, aiming to minimise shear and residual stress and thereby increase the resistance of the final product. …”
  3. 83

    An Artificial Neural Network for Online Tuning of Genetic Algorithm Based PI Controller for Interior Permanent Magnet Synchronous Motor–Drive by Rahman, M. A.

    Published 2006
    “…At each operating condition a genetic algorithm (GA) is used to optimize proportional-integral (PI) controller parameters in a closed loop vector control scheme. …”
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    article
  4. 84

    On the Optimization of Band Gaps in Periodic Waveguides by Jamil Renno (14070771)

    Published 2025
    “…Five nature-inspired optimization algorithms: Genetic Algorithm (GA), Differential Evolution (DE), Grey Wolf Optimizer (GWO), Improved Grey Wolf Optimizer (IGWO), and Particle Swarm Optimization (PSO) are compared. …”
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    GENETIC SCHEDULING OF TASK GRAPHS by Benten, M. S.

    Published 2020
    “…The problem of assigning tasks to processing elements as a combinatorital optimization is formulated, and a heuristic based on a genetic algorithm is presented. …”
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    article
  7. 87

    Timing driven genetic placement by Sait, Sadiq M.

    Published 2020
    “…IN this paper we present a timing driven placer for standard cell IC design. The placement algorithm follows the genetic paradigm, with the objective of minimizing both area and path slacks. …”
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    article
  8. 88

    Genetic Fuzzimetric Technique (GFT) by Kouatli, Issam

    Published 2012
    “…Integration of fuzzy systems with genetic algorithm has been identified by researchers as a useful technique of optimizing systems under uncertainty. …”
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  9. 89

    A Novel BIPV Reconfiguration Algorithm for Maximum Power Generation under Partial Shading by Saoud A. Al-Janahi (18877213)

    Published 2020
    “…The system is optimised for maximum yield to determine the optimal configuration and number of modules for each string using a genetic algorithm. …”
  10. 90

    Performance analysis and optimization of photovoltaic-thermal system with direct contact membrane distillation using metaheuristic algorithms by Faisal Maqbool (14561804)

    Published 2025
    “…The objective is to maximize electrical efficiency, permeate flux, and outlet temperature by considering the effects of flow rates (1–10 L/min), solar irradiation (10–1000 W/m2), and ambient temperatures (291–324 K). Metaheuristic algorithms, including Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), are employed to determine the optimal operating parameters. …”
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    Performance Assessment of Foraging Algorithms vs. Evolutionary Algorithms by El-Abd, Mohammed

    Published 2012
    “…This work provides a complete performance assessment of the four mentioned algorithms in comparison to the widely known differential evolution (DE), genetic algorithms (GAs), harmony search (HS), and particle swarm optimization (PSO) algorithms when applied to the problem of unconstrained nonlinear continuous function optimization. …”
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  13. 93

    Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization by Abu Zitar, Raed

    Published 2024
    “…This hybrid approach, the Improved Prairie Dog Optimization Algorithm (IPDOA) with the Genetic Algorithm (GA), utilizes the strengths of both algorithms to improve the overall optimization performance. …”
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    Using artificial bee colony to optimize software quality estimation models. (c2015) by Abou Assi, Tatiana Antoine

    Published 2016
    “…We compare our models to others constructed using other well established techniques such as C4.5, Genetic Algorithms, Simulated Annealing, Tabu Search, multi-layer perceptron with back-propagation, multi-layer perceptron hybridized with ABC and the majority classifier. …”
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