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  1. 1

    Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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    Article
  2. 2

    Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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    Thesis
  3. 3

    BAT-BP: A new BAT based back-propagation algorithm for efficient data classification by Mohd. Nawi, Nazri, M. Z., Rehman, Hafifi, Nurfarian, Khan, Abdullah, Siming, Insaf Ali

    Published 2016
    “…Thus, this study investigates the use of Bat algorithm along with back-propagation neural network (BPNN) algorithm in-order to gain optimal weights to solve the local minima problem and also to enhance the convergence rate. …”
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    Article
  4. 4

    A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting by Mohammed, Athraa Jasim, Ghathwan, Khalil Ibrahim, Yusof, Yuhanis

    Published 2020
    “…Even though Cuckoo Search has been proven to be able to solve global optimization in various areas, the algorithm leads to a slow convergence rate when the step size is large. …”
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    Article
  5. 5

    Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions by Mazlina, Abdul Majid, Alsariera, Yazan A., Alamri, Hammoudeh S., Nasser, Abdullah M., Kamal Z., Zamli

    Published 2014
    “…Owing to the fact that they are new and much of their relative performance are still unknown (as compared to other established meta-heuristic algorithms), Bacterial Foraging Optimization Algorithm (BFO) and Bat Algorithm (BA) have been adopted for comparison using the 12 selected benchmark functions. …”
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    Conference or Workshop Item
  6. 6

    Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2024
    “…Thus, this study proposed an Opposition-based Learning Binary Bat Algorithm as the feature selection technique in the T-method. …”
    Conference Paper
  7. 7

    In silico gene knockout prediction using a hybrid of Bat algorithm and minimization of metabolic adjustment by Man, Mei Yen, Mohd Saberi, Mohamad, Choon, Yee Wen, Mohd Arfian, Ismail

    Published 2021
    “…Gene knockout can be used to optimize the microbial strains, such as to maximize the production rate of chemicals of interest. …”
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    Article
  8. 8

    Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and bat algorithm by Shah, Abdul Salam, Mohamad Nasir, Haidawati, Fayaz, Muhammad, Lajis, Adidah, Ullah, Israr, Shah, Asadullah

    Published 2020
    “…We applied a deep extreme learning machine approach to predict the user parameters. We have used the Bat algorithm and fuzzy logic to optimize energy consumption and comfort index management. …”
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    Article
  9. 9

    Development of a Novel Hybrid Optimization Algorithm for Minimizing Irrigation Deficiencies by Valikhan-Anaraki, Mahdi, Mousavi, Sayed-Farhad, Farzin, Saeed, Karami, Hojat, Ehteram, Mohammad, Kisi, Ozgur, Fai, Chow Ming, Hossain, Md Shabbir, Hayder, Gasim, Ahmed, Ali Najah, El-Shafie, Amr H., Hashim, Huzaifa, Afan, Haitham Abdulmohsin, Lai, Sai Hin, El-Shafie, Ahmed

    Published 2019
    “…One of the most important issues in the field of water resource management is the optimal utilization of dam reservoirs. In the current study, the optimal utilization of the Aydoghmoush Dam Reservoir is examined based on a hybrid of the bat algorithm (BA) and particle swarm optimization algorithm (PSOA) by increasing the convergence rate of the new hybrid algorithm (HA) without being trapped in the local optima. …”
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    Article
  10. 10

    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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    Article
  11. 11

    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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    Article
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    Optimization of stiffened panel fatigue life by using finite element analysis by Mazlan, Shahan

    Published 2020
    “…Three optimization methods: screening, multi-objective genetic algorithm and adaptive multi-objective algorithm were adopted in this study. …”
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    Thesis
  14. 14

    A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network by Gumaida, Bassam, Abubakar, Adamu

    Published 2024
    “…Results: Simulation results perfectly showed that the suggested localization algorithm based on NMM can carry out a better performance than that of other localization algorithms utilizing other op- timization approaches, including a particle swarm optimization, ant colony (ACO) and bat algorithm (BA). …”
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    Article
  15. 15

    IWDSA: a hybrid Intelligent Water Drops with a Simulated Annealing for the localization improvement in wireless sensor networks by Gumaida, Bassam, Ibrahim, Adamu Abubakar

    Published 2024
    “…Additionally, simulation results confirm that the proposed algorithm IWDSA exhibits outstanding performance compared to other algorithms utilizing optimization techniques, including genetic algorithms, bat algorithms, ant colony optimization, and swarm optimization. …”
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    Article
  16. 16

    Hybrid MPPT algorithm for mismatch photovoltaic panel application / Muhammad Iqbal Mohd Zakki by Mohd Zakki, Muhammad Iqbal

    Published 2019
    “…MATLAB/Simulink is used to develop, test, optimize, and verify the proposed hybrid MPPT algorithm, and PSO-PID tuning method, before embedded in the MPPT system for the hardware implementation as a research product. …”
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    Thesis
  17. 17

    Optimization variation for multiple heuristic approaches in solar tracking by Fam D.F., Koh S.P., Tiong S.K., Chong K.H.

    Published 2023
    Subjects: “…Genetic algorithm…”
    Conference paper
  18. 18

    Performance analysis of PSO MPPT for photovoltaic (PV) system during irradiance changes / Kharismi Burhanudin by Burhanudin, Kharismi

    Published 2018
    “…Particle swarm optimization is soft computing methods which follow the bird swarm to track maximum power from PV panel. …”
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    Thesis
  19. 19

    Performance analyses of various photovoltaic power plant based on local spectral irradiances in Malaysia using genetic algorithm by Lim, Song Wei

    Published 2023
    “…Besides, the genetic algorithm has showed that it is an effective and efficient way to perform estimation of optimal tilt angle and orientation angle for solar sites with genetic algorithm as it is able to produce correct and accurate result in a short amount of time.…”
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    Final Year Project / Dissertation / Thesis
  20. 20

    Optimization of a reliable grid-connected PV-based power plant by Rashid, Muhammad Mahbubur, Ali, Mohammad Yeakub, Hasan, Muhammad Hasibul, Mokthar, Nur Syamimi

    Published 2023
    “…Maximum power point tracking (MPPT) has been used in this project in optimizing the PV system. One of the methods of the MPPT technique which is Perturb and Observe (P&O) algorithm, easy to implement and has efficient performance in solving the optimization problem. …”
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    Proceeding Paper