Search Results - ((colony algorithm) OR (((((mining algorithm) OR (search algorithm))) OR (bat algorithm))))

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  1. 1

    Dual level searching approach for solving multi objective optimisation problems using hybrid particle swarm optimisation and bats echolocation-inspired algorithms by Nafrizuan, Mat Yahya, A. R., Yusoff, Azlyna, Senawi, Tokhi, M. Osman

    Published 2019
    “…The concept of echolocation of a colony of bats to find prey in the modified adaptive bats sonar algorithm is integrated with the established particle swarm optimisation algorithm. …”
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    Article
  2. 2

    Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

    Published 2016
    “…The algorithm is a hybrid algorithm that operates using dual level search strategy that takes merits of a particle swarm optimisation algorithm and a modified adaptive bats sonar algorithm. …”
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    Thesis
  3. 3

    Multi-Swarm bat algorithm by Taha A.M., Chen S.-D., Mustapha A.

    Published 2023
    “…In this study a new Bat Algorithm (BA) based on multi-swarm technique called the Multi-Swarm Bat Algorithm (MSBA) is proposed to address the problem of premature convergence phenomenon. …”
    Article
  4. 4

    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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    Thesis
  5. 5

    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
    “…Over the last 30 years, many meta-heuristic algorithms have been developed in the literature including that of Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search Algorithm (HS) to name a few. …”
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  6. 6

    Seed disperser ant algorithm for optimization / Chang Wen Liang by Chang , Wen Liang

    Published 2018
    “…The Seed Disperser Ant Algorithm (SDAA) is developed based on the evolution or expansion process of Seed Disperser Ant (Aphaenogaster senilis) colony. …”
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    Thesis
  7. 7

    A new algorithm for normal and large-scale optimization problems: Nomadic People Optimizer by Alsewari, Abdul Rahman Ahmed, Sinan, Q. Salih

    Published 2019
    “…These algorithms faced an important issue, which is the balancing between the global search (exploration) and local search (exploitation) capabilities. …”
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    Article
  8. 8

    An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

    Published 2020
    “…Ant-Miner is a variant of ant colony optimisation and a prominent intelligent algorithm widely use in rules-based classification. …”
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    Thesis
  9. 9

    Improvement DACS3 Searching Performance using Local Search by Md Rais, Helmi, Ali Othman, Zulaiha, Hamdan, Abdul Razak

    Published 2009
    “…Several versions of metaheuristic ACOs’ have been developed through several improvement processes to produce better algorithm. Past research has proposed a Dynamic Ant Colony System with Three Level Updates (DACS3) algorithm that embedding a Malaysian House Red Ant behavior into current ACS. …”
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  10. 10

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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    Thesis
  11. 11

    Review of Multi-Objective Swarm Intelligence Optimization Algorithms by Yasear, Shaymah Akram, Ku Mahamud, Ku Ruhana

    Published 2021
    “…In this paper, the status of MOO research and state-of-the-art MOSI algorithms namely, multi-objective particle swarm, artificial bee colony, firefly algorithm, bat algorithm, gravitational search algorithm, grey wolf optimizer, bacterial foraging and moth-flame optimization algorithms have been reviewed. …”
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    Article
  12. 12

    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

    Published 2022
    “…The first modification enhances the initial population of the MBGWO using a heuristic based Ant Colony Optimisation algorithm. The second modification develops a new position update mechanism using the Bat Algorithm movement. …”
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  13. 13

    Acoustic emission partial discharge localization in oil based on artificial bee colony by Lim, Zhi Yang, Azis, Norhafiz, Mohd Hashim, Ahmad Hafiz, Mohd Radzi, Mohd Amran, Norsahperi, Nor Mohd Haziq, Mohd Ariffin, Azrul

    Published 2025
    “…Comparisons with the genetic algorithm (GA), particle swarm optimization (PSO) and bat algorithm (BA) revealed that the distance error, maximum deviation and computation time for AE PD localization based on ABC are the lowest. …”
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  14. 14

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

    Published 2018
    “…Firstly, a new strategy based on a combined method (i.e. single-objective Gravitational Search (GSA) with Bat Algorithm (BAT) (SOGS-BAT)) algorithm is proposed in which relies on the closed interval between 0 and 1 to avoid falling into local search. …”
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    Thesis
  15. 15

    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

    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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    Article
  17. 17

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

    Published 2020
    “…However, ACOC suffers from high diversification in which the algorithm cannot search for best solutions in the local neighbourhood. …”
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  18. 18

    Extended Bat Algorithm (EBA) as an improved searching optimization algorithm by Pebrianti, Dwi, Nurnajmin Qasrina, Ann, Luhur, Bayuaji, Nor Rul Hasma, Abdullah, Zainah, Md. Zain, Indra, Riyanto

    Published 2018
    “…This paper presents a new searching technique by using a new variant of Bat Algorithm (BA) known as Extended Bat Algorithm (EBA). …”
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    Book Chapter
  19. 19

    Lexicon-based and immune system based learning methods in Twitter sentiment analysis by Jantan, Hamidah, Drahman, Fatimatul Zahrah, Alhadi, Nazirah, Mamat, Fatimah

    Published 2016
    “…In future work, the accuracy of proposed model can be strengthened by comparative study with other heuristic based searching algorithms such as genetic algorithm, ant colony optimization, swam algorithms and etc.…”
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  20. 20

    Rule pruning techniques in the ant-miner classification algorithm and its variants: A review by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2018
    “…Rule-based classification is considered an important task of data classification.The ant-mining rule-based classification algorithm, inspired from the ant colony optimization algorithm, shows a comparable performance and outperforms in some application domains to the existing methods in the literature.One problem that often arises in any rule-based classification is the overfitting problem. …”
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