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  1. 1
    Performance evaluation of PID controller optimisation for wheel mobile robot using Bat based optimisation algorithm

    Performance evaluation of PID controller optimisation for wheel mobile robot using Bat based optimisation algorithm by ,, Dwi Pebrianti, Ann Ayop azmi, Nurnajmi Qasrina, Bayuaji, Luhur, Suarin, Nur Aisyah Syafinaz, ,, Muhammad Syafrullah

    Published 2022
    “…Three different optimization algorithms which are Bat Algorithm (BA), Bat Algorithm with Mutation (BAM) and Extended Bat Algorithm (EBA) are implemented to optimize the value of PID controller gain for wheel mobile robot. …”
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  2. 2
    PID controller design for mobile robot using Bat Algorithm with Mutation (BAM)

    PID controller design for mobile robot using Bat Algorithm with Mutation (BAM) by Pebrianti, Dwi, Indra, Riyanto, Bayuaji, Luhur, Muhammad Syafrullah, ., Arumgam, Yogesvaran, Nurnajmin Qasrina, Ann

    Published 2019
    “…Here, an optimization algorithm called Bat Algorithm with Mutation (BAM) is proposed to optimize the value of PID controller gain for mobile robot. …”
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  3. 3
    Multi-Robot Learning with Bat Algorithm With Mutation (Bam)

    Multi-Robot Learning with Bat Algorithm With Mutation (Bam) by Chandrathevan, Sathiamurthy

    Published 2022
    “…BAT algorithm is implemented to achieve the target. …”
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  4. 4
    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
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  5. 5
    A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds

    A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds by Salim, Naomie, Shah, J. Z.

    Published 2007
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  6. 6
    Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali

    Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali by Ihsan , Ali

    Published 2024
    “…To address relay node selection and data scheduling issues, Energy-Efficient Scheduling (EES) and Energy-Efficient Un-Scheduling (EEUS) methods have been introduced using the Improved Discrete Bat Algorithm (IDBA) along with the Adaptive Warshal Floyd algorithm (AWF). …”
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  7. 7
    Enhancement Of Clustering Algorithm Using 3D Euclidean Distance To Improve Network Connectivity In Wireless Sensor Networks For Correlated Node Behaviours

    Enhancement Of Clustering Algorithm Using 3D Euclidean Distance To Improve Network Connectivity In Wireless Sensor Networks For Correlated Node Behaviours by Kalid Abdlkader Marsal Salih

    Published 2024
    thesis::doctoral thesis
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  8. 8
    Modified ACS centroid memory for data clustering

    Modified ACS centroid memory for data clustering by Jabbar, Ayad Mohammed, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2019
    “…A comparison of the performance of several common clustering algorithms using real-world data sets shows that the accuracy of the proposed algorithm surpasses those of its counterparts.…”
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  9. 9
    An improved ACS algorithm for data clustering

    An improved ACS algorithm for data clustering by Mohammed Jabbar, Ayad, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2020
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  10. 10
    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
    “…Thus, it can be concluded that QEEA algorithm is the most energy efficient and the best candidate for provisioning the QoS for the real time (RT) and non-real time (NRT) applications.…”
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  11. 11
    A partition based feature selection approach for mixed data clustering / Ashish Dutt

    A partition based feature selection approach for mixed data clustering / Ashish Dutt by Ashish , Dutt

    Published 2020
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  12. 12
    Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation

    Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation by Tan , Khang Siang

    Published 2011
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  13. 13
    Max-D clustering K-means algorithm for Autogeneration of Centroids and Distance of Data Points Cluster

    Max-D clustering K-means algorithm for Autogeneration of Centroids and Distance of Data Points Cluster by Wan Maseri, Wan Mohd, Beg, Abul Hashem, Tutut, Herawan, K., F.Rabbi

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  14. 14
    Clustering chemical data set using particle swarm optimization based algorithm

    Clustering chemical data set using particle swarm optimization based algorithm by Triyono, Triyono

    Published 2008
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  15. 15
    MGR: An Information Theory Based Hierarchical Divisive Clustering Algorithm for Categorical Data

    MGR: An Information Theory Based Hierarchical Divisive Clustering Algorithm for Categorical Data by Hongwu, Qin, Ma, Xiuqin, Herawan, Tutut, Jasni, Mohamad Zain

    Published 2014
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  16. 16
    Integrated bisect K-means and firefly algorithm for hierarchical text clustering

    Integrated bisect K-means and firefly algorithm for hierarchical text clustering by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2016
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  17. 17
    Beta Distribution Weighted Fuzzy C-Ordered-Means Clustering

    Beta Distribution Weighted Fuzzy C-Ordered-Means Clustering by Hengda, Wang, Mohamad Mohsin, Mohamad Farhan, Mohd Pozi, Muhammad Syafiq

    Published 2024
    “…The fuzzy C-ordered-means clustering (FCOM) is a fuzzy clustering algorithm that enhances robustness and clustering accuracy through the ordered mechanism based on fuzzy C-means (FCM). …”
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  18. 18
    Hybrid Henry gas solubility optimization algorithm with dynamic cluster-to-algorithm mapping

    Hybrid Henry gas solubility optimization algorithm with dynamic cluster-to-algorithm mapping by Kamal Z., Zamli, Kader, Md. Abdul, Azad, Saiful, Ahmed, Bestoun S.

    Published 2021
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  19. 19
    Clustering of Chemical Compounds using Unsupervised Neural Networks Algorithms: a comparison

    Clustering of Chemical Compounds using Unsupervised Neural Networks Algorithms: a comparison by Zeb Shah, Jehan, Salim, Naomie

    Published 2006
    “…In this work the applications of a number of self-organizing map (SOM) neural network algorithms to the clustering of chemical datasets are investigated. …”
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  20. 20
    Clustering of chemical compounds using unsupervised neural networks algorithms : a comparison

    Clustering of chemical compounds using unsupervised neural networks algorithms : a comparison by Zeb Shah, Jehan, Salim, Naomie

    Published 2006
    “…In this work the applications of a number of self-organizing map (SOM) neural network algorithms to the clustering of chemical datasets are investigated. …”
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