Search Results - (( initial optimization bat algorithm ) OR ( data distribution function algorithm ))

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  1. 1

    An improved bat algorithm with artificial neural networks for classification problems by Rehman Gillani, Syed Muhammad Zubair

    Published 2016
    “…Recently, a new metaheuristic search Bat algorithm has become quite popular due its tendency towards convergence to optimal points in the search trajectory by using echo-location behavior of bats as its random walk. …”
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  2. 2

    An improved genetic bat algorithm for unconstrained global optimization problems by Muhammad Zubair, Rehman, Kamal Z., Zamli, Abdullah, Nasser

    Published 2020
    “…Therefore, to ensure that GA converges to a global solution, this paper proposed a two-stage improved Genetic Bat algorithm (GBa) in which the GA finds the optimal solution first and then Bat starts from where the GA has converged. …”
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  3. 3

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

    Published 2024
    “…The Modified Adaptive Bats Sonar Algorithm (MABSA), initially designed for single objective optimization and inspired by colony bats' echolocation, has demonstrated efficiency with its simple structure and reduced computation time. …”
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  4. 4

    A hybrid bat–swarm algorithm for optimizing dam and reservoir operation by Yaseen, Zaher Mundher, Allawi, Mohammed Falah, Karami, Hojat, Ehteram, Mohammad, Farzin, Saeed, Ahmed, Ali Najah, Koting, Suhana, Mohd, Nuruol Syuhadaa, Jaafar, Wan Zurina Wan, Afan, Haitham Abdulmohsin, El-Shafie, Ahmed

    Published 2019
    “…This study proposes a new hybrid optimization algorithm based on a bat algorithm (BA) and particle swarm optimization algorithm (PSOA) called the hybrid bat–swarm algorithm (HB-SA). …”
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    Article
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    A Navigation Strategy for Swarm Robotics Based on Bat Algorithm Optimization Technique by Nur Aisyah Syafinaz, Suarin, Pebrianti, Dwi, Bayuaji, Luhur, Muhammad, Syafrullah, Zulkifli, Musa

    Published 2018
    “…This paper aims to adapt Bat Algorithm (BA) optimization techniques to the swarm robotics system. …”
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  7. 7

    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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    A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition by Koh J.S., Tan R.H.G., Lim W.H., Tan N.M.L.

    Published 2024
    “…Extensive studies prove the proposed algorithm outperforms bat algorithm (BA), improved grey wolf optimizer (IGWO), conventional PSO and P&O, with convergence time shorter than 0.3 s and tracking accuracy above 99% under different complex PSCs. � 2010-2012 IEEE.…”
    Article
  10. 10

    Multi-Objective Optimal Energy Management of Nanogrid Using Improved Pelican Optimization Algorithm by Jamal S., Pasupuleti J., Rahmat N.A., Tan N.M.L.

    Published 2025
    “…In order to demonstrate the effectiveness of the proposed algorithm, The outcomes of the simulation are juxtaposed with results obtained from the initial Pelican Optimisation Algorithm (POA), the Bat Algorithm, and the Improved Differential Evolutionary (IDE) Algorithm. …”
    Article
  11. 11

    Analysis the effectiveness of cryogenic treatment through roughness and temperature prediction using bonn technique / Manjunath.S and Ajay Kumar by S., Manjunath, Ajay, Kumar

    Published 2017
    “…For the optimization process, the cutting tool is initially subjected to cryogenic treatment for the improvement in the tool property. …”
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    Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm by Suparman, S., Rusiman, Mohd Saifullah

    Published 2018
    “…In the hierarchical Bayesian approach, the order and coefficients of the autoregressive model are assumed to have a prior distribution. The prior distribution is combined with the likelihood function to obtain a posterior distribution. …”
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    Article
  14. 14

    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…Thereafter, a multi-objective hybrid algorithm (MOHA), an extension of the self-adaptive hybrid algorithm is proposed and tested on the established multi-objective (MO) test functions. …”
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  15. 15

    A new Gompertz-three-parameter-lindley distribution for modeling survival time data by Liang, Fei, Lu, Hezhi, Xi, Yuhang

    Published 2025
    “…The statistical properties of the proposed distribution including the shape properties, cumulative distribution, quantile functions, moment generating function, failure rate function, mean residual function, and stochastic orders are studied. …”
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  16. 16

    Reliability Analysis and Prediction of Time to Failure Distribution of an Automobile Crankshaft by Salvinder Singh, Karam Singh, Shahrum, Abdullah, Nik Abdullah, Nik Mohamed

    Published 2015
    “…The developed stochastic algorithm has the capability to measure the parametric distribution function and validate the predict the reliability rate, mean time to failure and hazard rate. …”
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  17. 17

    Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

    Published 2019
    “…The main contribution of this research is developing statistical approaches, and introducing new algorithms and resampling methods for analysing interval-censored data through AFT models.…”
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  18. 18

    Slice sampler algorithm for generalized pareto distribution by Rostami, Mohammad, Adam, Mohd Bakri, Yahya, Mohamed Hisham, Ibrahim, Noor Akma

    Published 2018
    “…In this paper, we developed the slice sampler algorithm for the generalized Pareto distribution (GPD) model. …”
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  19. 19

    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

    Published 2014
    “…In order to evaluate the scalability at specific data size the appropriate regression models are fitted through the measured data as functions of number of workers. …”
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  20. 20

    Parameter-driven count time series models / Nawwal Ahmad Bukhari by Nawwal , Ahmad Bukhari

    Published 2018
    “…A key property of our model is that the distributions of the observed count data are independent, conditional on the latent process, although the observations are correlated marginally. …”
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