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  1. 1

    Improved Bat Algorithm for faster convergence in solving optimisation problem by Ramli, Mohamad Raziff

    Published 2021
    “…In this study, one of the metaheuristic algorithms known as the Bat Algorithm (BA) has been discussed. …”
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  2. 2

    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems by Nor Shuhada, Ibrahim

    Published 2024
    “…Subsequently, it is exploring into the development of random approaches based on MABSA, integrating components into others algorithm whereby Squirrel Search Algorithm (SSA), Cauchy Mutation (CM) approach, and Doppler Effect (DE) phenomenon. …”
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  3. 3

    Extended bat algorithm for PID controller tuning of wheeled mobile robot and swarm robotics target searching strategy by Nur Aisyah Syafinaz, Suarin

    Published 2020
    “…Extended Bat Algorithm (EBA) has been chosen as swarm intelligent based method for this research study. …”
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  4. 4

    A bat-inspired t-way strategy for mixed-strength test suite generation by Ahmad, Yazan Sadeq Al Sariera

    Published 2017
    “…BTS is the first t-way strategy that adopts the Bat-inspired algorithm as its core implementation and adopts the Hamming distance as the final selection criteria to enhance the exploration of new solution. …”
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  5. 5

    Quantum-based analytical techniques on the tackling of well placement optimization by Islam, J., Negash, B.M., Vasant, P.M., Hossain, N.I., Watada, J.

    Published 2020
    “…Furthermore, statistical analysis shows that there is no statistical difference between the performance of Quantum bat algorithm and Quantum Particle swarm optimization algorithm. …”
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  6. 6

    Quantum-based analytical techniques on the tackling of well placement optimization by Islam, J., Negash, B.M., Vasant, P.M., Hossain, N.I., Watada, J.

    Published 2020
    “…Furthermore, statistical analysis shows that there is no statistical difference between the performance of Quantum bat algorithm and Quantum Particle swarm optimization algorithm. …”
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  7. 7

    Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali by Ihsan , Ali

    Published 2024
    “…The IDBA-AFW evaluates the fitness of relay nodes based on multiple criteria, such as energy efficiency, throughput, and end-to-end delay. Both Bat Algorithm parameters and AFW parameters are adaptively tuned to balance exploration and exploitation throughout the optimization process. …”
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  8. 8

    A new algorithm for normal and large-scale optimization problems: Nomadic People Optimizer by Alsewari, Abdul Rahman Ahmed, Sinan, Q. Salih

    Published 2019
    “…These algorithms faced an important issue, which is the balancing between the global search (exploration) and local search (exploitation) capabilities. …”
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  9. 9
  10. 10

    Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm by Ehteram, Mohammad, P. Singh, Vijay, Karami, Hojat, Hosseini, Khosrow, Dianatikhah, Mojgan, Hossain, Md., Ming Fai, Chow, El-Shafie, Ahmed

    Published 2018
    “…For example, the average solution for the IWA at high inflow was 0.985 while it was 1.037, 1.040, 1.115 and 1.121 for the weed algorithm (WA), bat algorithm (BA), improved particle swarm optimization algorithm (IPSOA) and genetic algorithm (GA). …”
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  11. 11

    Application of augmented bat algorithm with artificial neural network in forecasting river inflow of hydroelectric reservoir stations in Malaysia by Joe Wee Wei, Mr.

    Published 2023
    “…However, standalone models, such as Artificial Neural Network (ANN), typically underperform during local convergence and resulted in slow-speed convergence. Thus, Bat Algorithm (BA) was used to enhance the efficiency of ANN in forecasting upstream river SF, as BA is capable of switching from the “explore to exploit” function which could increase the rate of convergence at the initial stage and deliver a quick result for a majority of a classification problem. …”
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  13. 13

    A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites by Din, Fakhrud

    Published 2019
    “…Many test data generation strategies based on meta-heuristic algorithms such as Simulated Annealing (SA), Tabu Search (TS), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search (HS), Cuckoo Search (CS), Bat Algorithm (BA) and Bees Algorithm have been developed in recent years. …”
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  14. 14