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  1. 281

    Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification by Rajendra Babu Chikkala (22330876)

    Published 2025
    “…The BRNN model, refined using the Adagrad optimization algorithm, efficiently integrates the learned features from both branches. …”
  2. 282

    A modified coronavirus herd immunity optimizer for capacitated vehicle routing problem by Abu Zitar, Raed

    Published 2021
    “…Due to the complex nature of the capacitated vehicle routingproblem, metaheuristic optimization algorithms are widely used for tackling this type of challenge.Coronavirus Herd Immunity Optimizer (CHIO) is a recent metaheuristic population-based algorithm thatmimics the COVID-19 herd immunity treatment strategy. …”
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  3. 283

    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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  4. 284

    Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm by Youssef, H.

    Published 2020
    “…In this paper, we present an approach based on Simulated Evolution algorithm for the design of SEN topology. …”
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  5. 285

    Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm by Youssef, H.

    Published 2020
    “…In this paper, we present an approach based on Simulated Evolution algorithm for the design of SEN topology. …”
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    article
  6. 286

    A Review on Swarm Intelligence and Evolutionary Algorithms for Solving the Traffic Signal Control Problem by Shaikh, Palwasha

    Published 2020
    “…This paper conducts a comprehensive literature review on applications of evolutionary and swarm intelligence algorithms to TSC. Surveyed work is categorized based on the set of decision variables, optimization objective(s), problem modeling and solution encoding. …”
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  7. 287

    Improving Neural Network Using Jaya Algorithm with Opposite Learning for Air Quality Prediction by Abdullah, Afsah

    Published 2024
    “…In this paper, an enhanced Jaya optimization algorithm is used to improve the MLP outcome (called EOL-Jaya-MLP). …”
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  8. 288

    Improving Neural Network Using Jaya Algorithm with Opposite Learning for Air Quality Prediction by Abdullah, Afsah

    Published 2024
    “…In this paper, an enhanced Jaya optimization algorithm is used to improve the MLP outcome (called EOL-Jaya-MLP). …”
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  9. 289

    Improving Neural Network Using Jaya Algorithm with Opposite Learning for Air Quality Prediction by Abdullah, Afsah

    Published 2024
    “…In this paper, an enhanced Jaya optimization algorithm is used to improve the MLP outcome (called EOL-Jaya-MLP). …”
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  10. 290

    Improving Neural Network Using Jaya Algorithm with Opposite Learning for Air Quality Prediction by Abdullah, Afsah

    Published 2024
    “…In this paper, an enhanced Jaya optimization algorithm is used to improve the MLP outcome (called EOL-Jaya-MLP). …”
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  11. 291

    Improving Neural Network Using Jaya Algorithm with Opposite Learning for Air Quality Prediction by Abdullah, Afsah

    Published 2024
    “…In this paper, an enhanced Jaya optimization algorithm is used to improve the MLP outcome (called EOL-Jaya-MLP). …”
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  12. 292

    Genetic Algorithm Analysis using the Graph Coloring Method for Solving the University Timetable Problem by Haraty, Ramzi A.

    Published 2018
    “…Genetic algorithms were successfully useful to solve many optimization problems including the university Timetable Problem. …”
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  13. 293

    Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing by Jincheng Zhou (1887307)

    Published 2023
    “…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …”
  14. 294

    Minimum UAV fog servers with maximum IoT devices association using genetic algorithms by Abbas, Nadine

    Published 2021
    “…We then propose a heuristic sub-optimal approach based on genetic algorithm (GA) to decide on the minimum number of UAVs to be deployed and the IoT-to-UAV association. …”
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  15. 295

    Power-constrained system-on-a-chip test scheduling using a genetic algorithm by Harmanani, Haidar M.

    Published 2006
    “…This paper presents an efficient approach for the test scheduling problem of core-based systems based on a genetic algorithm. The method minimizes the overall test application time of a system-on-a-chip through efficient and compact test schedules. …”
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  16. 296

    An enhanced binary artificial rabbits optimization for feature selection in medical diagnosis by Al-Betar, Mohammed Azmi

    Published 2023
    “…ARO is a recent swarm-based optimization algorithm that mimics rabbits’ natural survival tactics and eating habits. …”
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  17. 297
  18. 298

    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. …”
  19. 299

    Optimization of Battery Electric Bus Charging under Varying Operating Conditions by Basma, Hussein

    Published 2020
    “…This paper proposes an optimization algorithm based on Dynamic Programming that minimizes the total BEB energy costs and battery replacement costs by optimally controlling the BEB daily charging power throughout the year, considering the varying operating conditions. …”
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  20. 300

    A new minimum curvator multi-step method for unconstrained optimization by Obeid, Samir

    Published 1998
    “…Our derivation of the new algorithm is based on determining some value of the parameter that minimizes the curvature in some chosen metric. …”
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