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  1. 1
    Comfort and energy consumption optimization in smart homes using bat algorithm with inertia weight

    Comfort and energy consumption optimization in smart homes using bat algorithm with inertia weight by Mohamad Razwan, Abdul Malek, Nor Azlina, Ab. Aziz, Alelyani, Salem, Mohana, Mohamed, Farah Nur Arina, Baharudin, Zuwairie, Ibrahim

    Published 2022
    “…Moreover, the comfort level achieved by BA with exponential inertia weight is found to be better than previously reported works using firefly algorithm, genetic algorithm, ant colony optimization, and artificial bee colony algorithm. …”
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  2. 2
    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
    “…The performance of the proposed Bat-BP algorithm is then compared with Artificial Bee Colony using BPNN (ABC-BP), Artificial Bee Colony using Levenberg-Marquardt (ABC-LM) and BPNN algorithm. …”
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  3. 3
    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions

    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

    Published 2018
    “…Secondly, two meta-heuristics, namely, Bi-Objective Gravitational Search Algorithm (BOGSA) and Bi-Objective Bat Algorithm (BOBAT), were combined to form a (BOGS-BAT) algorithm. …”
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  4. 4
    Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm

    Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm by Muhammad Syahril Mohamad Sainal

    Published 2022
    “…This research will conduct comparison of hybrid Genetic Algorithm and Bat Algorithm (GA-BA) with Genetic Algorithm (GA) and Bat Algorithm (BA). …”
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  5. 5
    An improved dynamic load balancing for virtualmachines in cloud computing using hybrid bat and bee colony algorithms

    An improved dynamic load balancing for virtualmachines in cloud computing using hybrid bat and bee colony algorithms by Ullah, Arif

    Published 2021
    “…Therefore, to overcome these problems, this study proposed an improved dynamic load balancing technique known as HBAC algorithm which dynamically allocates task by hybridizing Artificial Bee Colony (ABC) algorithm with Bat algorithm. …”
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  6. 6
    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
    “…In other words, the implemented bat algorithm in neural network structure is to get global optimization in order to minimize mean absolute percentage error, MAPE. …”
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  7. 7
    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
    “…In other words, the implemented bat algorithm in neural network structure is to get global optimization in order to minimize mean absolute percentage error, MAPE. …”
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  8. 8
    HEURISTIC OPTIMIZATION OF BAT ALGORITHM FOR HETEROGENEOUS SWARMS USING PERCEPTION

    HEURISTIC OPTIMIZATION OF BAT ALGORITHM FOR HETEROGENEOUS SWARMS USING PERCEPTION by Kappagantula, S., Vojjala, S., Iyer, A.A., Velidi, G., Emani, S., Vandrangi, S.K.

    Published 2023
    “…Swarm Intelligence is inspired by naturally occurring swarm systems suchas Ant Colony, Bees Hive, or Bats. The Bat Algorithm is a population-based meta-heuristic algorithm for solving continuous optimization problems. …”
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  9. 9
    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…The firefly algorithm remains a feasible alternative for shallow architectural network models, while metaheuristic algorithms such as the Particle swarm algorithm and Bat algorithm are better options for deeper architectural network models. …”
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  10. 10
    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
    “…Hence, to enhance the search ability of Cuckoo Search, it is integrated with Bat algorithm that offers a balanced search between global and local. …”
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  11. 11
    Optimizing dam and reservoir operations using machine learning

    Optimizing dam and reservoir operations using machine learning by Mohammad Abdullah Adib Almubaidin

    Published 2025
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  12. 12
    Application of Bat Algorithm and Its Modified Form Trained with ANN in Channel Equalization

    Application of Bat Algorithm and Its Modified Form Trained with ANN in Channel Equalization by Pradyumna Kumar Mohapatra, Saroja Kumar Rout, Sukant Kishoro Bisoy, Sandeep Kautish, Muzaffar Hamzah, Muhammed Basheer Jasser, Ali Wagdy Mohamed

    Published 2022
    “…Experimental and statistical analyses show that, in comparison with the bat as well as variants of the bat and state-of-the-art algorithms, the proposed algorithm substantially outperforms them significantly, based on MSE and BER.…”
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  13. 13
    Assessing the predictability of an improved ANFIS model for monthly streamflow using lagged climate indices as predictors

    Assessing the predictability of an improved ANFIS model for monthly streamflow using lagged climate indices as predictors by Ehteram M., Afan H.A., Dianatikhah M., Ahmed A.N., Fai C.M., Hossain M.S., Allawi M.F., Elshafie A.

    Published 2023
    “…Climate models; Climatology; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Mean square error; Particle swarm optimization (PSO); Principal component analysis; Stream flow; Adaptive neuro-fuzzy inference system; ANFIS-PSO; Climate index; Confidence levels; ENSO; Probability spaces; Root mean square errors; Streamflow simulations; Fuzzy inference; assessment method; El Nino-Southern Oscillation; genetic algorithm; index method; model; prediction; seasonal variation; streamflow; uncertainty analysis…”
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  14. 14
    Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function

    Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function by Hammash, Nayif Mohammed

    Published 2012
    “…This means that it spends a long time for the bees algorithm converge the optimum solution. …”
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  15. 15
    Data clustering using the bees algorithm

    Data clustering using the bees algorithm by Pham, D.T, Otri, S., Afify, A., Mahmuddin, Massudi, Al-Jabbouli, H.

    Published 2007
    “…This paper proposes a clustering method that integrates the simplicity of the k-means algorithm with the capability of the Bees Algorithm to avoid local optima. …”
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  16. 16
    Enhanced Bat Algorithm for Solving Non-Convex Economic Dispatch Problem

    Enhanced Bat Algorithm for Solving Non-Convex Economic Dispatch Problem by Hussain, K., Zhu, W., Salleh, M.N.M., Ali, H., Talpur, N., Naseem, R., Ahmad, A., Ullah, A.

    Published 2020
    “…Bat algorithm lags behind other modern metaheuristic algorithms in terms of search efficiency, due to premature convergence. …”
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  17. 17
    Enhanced Bat Algorithm for Solving Non-Convex Economic Dispatch Problem

    Enhanced Bat Algorithm for Solving Non-Convex Economic Dispatch Problem by Hussain, K., Zhu, W., Salleh, M.N.M., Ali, H., Talpur, N., Naseem, R., Ahmad, A., Ullah, A.

    Published 2020
    “…Bat algorithm lags behind other modern metaheuristic algorithms in terms of search efficiency, due to premature convergence. …”
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  18. 18
    Fuzzy Systems and Bat Algorithm for Exergy Modeling in a Gas Turbine Generator

    Fuzzy Systems and Bat Algorithm for Exergy Modeling in a Gas Turbine Generator by Alemu Lemma, Tamiru, Mohd Hashim, Fakhruldin

    Published 2011
    “…The fuzzy models are trained applying locally linear model tree algorithm followed by a meta-heuristic nature inspired algorithm called bat algorithm. …”
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  19. 19
    A near-optimal centroids initialization in K-means algorithm using bees algorithm

    A near-optimal centroids initialization in K-means algorithm using bees algorithm by Mahmuddin, Massudi, Yusof, Yuhanis

    Published 2009
    “…The K-mean algorithm is one of the popular clustering techniques.The algorithm requires user to state and initialize centroid values of each group in advance. …”
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  20. 20
    Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management

    Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management by Julius, Beneoluchi Odili, M. N. M., Kahar, Noraziah, Ahmad, M., Zarina, Riaz, Ul Haq

    Published 2017
    “…After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. …”
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