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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
    Voting algorithms for large scale fault-tolerant systems

    Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

    Published 2011
    “…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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  9. 9
    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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  10. 10
    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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  11. 11
    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms

    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

    Published 2015
    “…This was achieved by mitigating convergence in the genetic algorithms by employing a hierarchical parallel architecture. …”
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  12. 12
    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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  13. 13
    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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  14. 14
    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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  15. 15
    Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes

    Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes by Mohammad Sigit Arifianto, Tze, Kenneth Kin Teo, Liau, Chung Fan, Liawas Barukang, Zaturrawiah Ali Omar

    Published 2007
    “…Genetic Algorithm as one of the Evolutionary Computation method improve the execution of parallel programming codes by optimizing the number of processors and the distribution of data. …”
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    Research Report
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  16. 16
    Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design

    Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design by Haohao, Ma, As’arry, Azizan, Yanwei, Feng, Lulu, Cheng, Delgoshaei, Aidin, Ismail, Mohd Idris Shah, Ramli, Hafiz Rashidi

    Published 2024
    “…This paper presents a comprehensive study on the design optimization of a robotic gripper, focusing on both the gripper modeling and the optimization of its parallel mechanism structure. …”
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  17. 17
    Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems

    Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems by Uvaraja, Vikneswary

    Published 2018
    “…Additionally, the MTS algorithm is also implemented in parallel computing to produce parallel MTS for generating comparable solutions in shorter computational times. …”
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  18. 18
    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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  19. 19
    Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil

    Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil by Ahmad, Ahmad Firdaus

    Published 2014
    “…Examples of EC such as Genetic Algorithm (GA) and PSO (Particle Swarm Optimization) are prevalent due to their efficiency and effectiveness. …”
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  20. 20
    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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