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  1. 1
    Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin

    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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  2. 2
    Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin

    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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  3. 3
    BAT-BP: A new BAT based back-propagation algorithm for efficient data classification

    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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  4. 4
    A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting

    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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  5. 5
    Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions

    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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  6. 6
    Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method

    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. …”
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  7. 7
    In silico gene knockout prediction using a hybrid of Bat algorithm and minimization of metabolic adjustment

    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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  8. 8
    Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and bat algorithm

    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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  9. 9
    Development of a Novel Hybrid Optimization Algorithm for Minimizing Irrigation Deficiencies

    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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  10. 10
    Quantum-based analytical techniques on the tackling of well placement optimization

    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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  11. 11
    Quantum-based analytical techniques on the tackling of well placement optimization

    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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  12. 12
    A miniature stub-loaded antenna optimized at VHF band for FSR sensor application / Hasrul Hisyam Harun

    A miniature stub-loaded antenna optimized at VHF band for FSR sensor application / Hasrul Hisyam Harun by Harun, Hasrul Hisyam

    Published 2014
    “…This article demonstrated a miniature monopole antenna optimization at VHF band (30-300MHz) for FSR sensor application. …”
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  13. 13
    Iterative And Single-Step Solutions Of Two Dimensional Time-Domain Inverse Scattering Problem Featuring Ultra Wide Band Sensors

    Iterative And Single-Step Solutions Of Two Dimensional Time-Domain Inverse Scattering Problem Featuring Ultra Wide Band Sensors by Binajjaj, Saeed Ali Saeed

    Published 2010
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  14. 14
    Development of a novel hybrid optimization algorithm for minimizing irrigation deficiencies

    Development of a novel hybrid optimization algorithm for minimizing irrigation deficiencies by Valikhan-Anaraki M., Mousavi S.-F., Farzin S., Karami H., Ehteram M., Kisi O., Fai C.M., Hossain M.S., Hayder G., Ahmed A.N., El-Shafie A.H., Bin Hashim H., Afan H.A., Lai S.H., El-Shafie A.

    Published 2023
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  15. 15
    A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network

    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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  16. 16
    IWDSA: a hybrid Intelligent Water Drops with a Simulated Annealing for the localization improvement in wireless sensor networks

    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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  17. 17
    Machine learning in botda fibre sensor for distributed temperature measurement

    Machine learning in botda fibre sensor for distributed temperature measurement by Nur Dalilla binti Nordin

    Published 2023
    “…The results obtained in these experiments would provide some overview in deploying machine learning algorithm for characterizing the Brillouin-based fibre sensor signals.…”
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  18. 18
    Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset

    Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset by Amirruddin, A., Aziz, I.A., Hasan, M.H.

    Published 2020
    “…SVR however is inferior in accuracy and thus this paper discusses the usage of an optimized SVR with Evolved Bat Algorithm (EBA) to handle the missing value accurately with high execution time. …”
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  19. 19
    Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff

    Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff by Mohd Yusoff, Nurulanis

    Published 2017
    “…Hence, efficient solutions are necessary to optimize EE and at the same time achieve high data rates to meet green LTE requirements. …”
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  20. 20
    Efficient and scalable ant colony optimization based WSN routing protocol for IoT

    Efficient and scalable ant colony optimization based WSN routing protocol for IoT by Sharmin, Afsah, Anwar, Farhat, Motakabber, S. M. A.

    Published 2020
    “…For this reason, many intelligent systems have been utilized to design routing algorithms to handle the network's dynamic state. In this paper, an ant colony optimization (ACO) based WSN routing algorithm for IoT has been proposed and analyzed to enhance scalability, to accommodate node mobility and to minimize initialization delay for time critical applications in the context of IoT to find the optimal path of data transmission, improvising efficient IoT communications. …”
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