Search Results - (( using optimisation based algorithm ) OR ( using identification using algorithm ))

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  1. 1

    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. …”
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    Thesis
  2. 2

    Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

    Published 2020
    “…Many optimisation-based intrusion detection algorithms have been developed and are widely used for intrusion identification. …”
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    Article
  3. 3

    Date store management in sliding window based on-line identification algorithms by Asirvadam , Vijanth Sagayan, McLoone, Sean, Irwin, George W

    Published 2001
    “…Sliding window identification algorithms use information from a store of data to optimise on-line learning. …”
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    Conference or Workshop Item
  4. 4

    NARX modelling for steam distillation pilot plant using binary particle swarm optimisation technique / Najidah Hambali by Hambali, Najidah

    Published 2019
    “…This study proposes a system identification of SDPP using NARX model. The model structure selection of polynomial NARX had been focused on Binary Particle Swarm Optimisation (BPSO) algorithm. …”
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    Thesis
  5. 5

    Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation by Illias, Hazlee Azil, Wee, Zhao Liang

    Published 2018
    “…In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. …”
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    Article
  6. 6

    Linear-pso with binary search algorithm for DNA motif discovery / Hazaruddin Harun by Harun, Hazaruddin

    Published 2015
    “…Particle Swarm Optimisation (PSG) was selected as the base algorithm that needs improvement and integration with other techniques. …”
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    Thesis
  7. 7

    Linear-PSO with binary search algorithm for DNA Motif Discovery / Hazaruddin Harun by Harun, Hazaruddin

    Published 2015
    “…Particle Swarm Optimisation (PSO) was selected as the base algorithm that needs improvement and integration with other techniques. …”
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    Book Section
  8. 8

    Plant leaf recognition algorithm using ant colony-based feature extraction technique by Ghasab, Mohammad Ali Jan

    Published 2013
    “…Then, based on the characteristics of each species, decision making is done by means of ant colony optimisation as a search algorithm to return the optimal subset of features regarding the related species. …”
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    Thesis
  9. 9

    INTELLIGENT MODELLING OF GRADIENT FLEXIBLE PLATE STRUCTURE UTILISING HYBRID EVOLUTIONARY ALGORITHM by Muhammad Hasbollah, Hassan

    Published 2023
    “…First, evolutionary algorithms, namely particle swarm optimisation (PSO) and grey wolf optimisation (GWO) were used in developing GFPS dynamic model and their performances were compared. …”
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    Thesis
  10. 10

    Identifying communities with modularity metric using Louvain and Leiden algorithms by Shibghatullah, Abdul Samad, Hairol Anuar, Siti Haryanti, Abal Abas, Zuraida, Md Yunos, Norhazwani, Setiad, Tedy, Mukhtar, Mohd Fariduddin

    Published 2024
    “…Among them, the optimisation methods are widely focused on. This paper focuses on an empirical study of two community detection algorithms based on agglomerative techniques using modularity metric: Louvain and Leiden. …”
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    Article
  11. 11

    RFID data reliability optimiser based on two dimensions bloom filter by Yaacob, Siti Salwani, Mahdin, Hairulnizam, Kasim, Shahreen

    Published 2017
    “…RFID system used radio waves to perform wireless interaction to detect and read data from the tagged object. …”
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    Article
  12. 12
  13. 13

    Dynamic modelling of a flexible beam structure using feedforward neural networks for active vibration control by Tuan Abdul Rahman, Tuan Ahmad Zahidi, As'arry, Azizan, Abdul Jalil, Nawal Aswan, Raja Ahmad, Raja Mohd Kamil

    Published 2019
    “…A non-parametric modelling approach of the system was proposed based on feed-forward neural networks (FNNs) while its weight and bias parameters were optimised using chaotic-enhanced stochastic fractal search (SFS) algorithm. …”
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    Article
  14. 14

    Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation by Toha, Siti Fauziah, Abd Latiff, I., Mohamad, M., Tokhi, M Osman

    Published 2009
    “…The proposed method formulates a modified inertia weight algorithm by using a dynamic spread factor (SF). The inertia weight plays an important role in terms of balancing both the global and local search. …”
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    Proceeding Paper
  15. 15

    Rockfall source identification using a hybrid Gaussian mixture-ensemble machine learning model and LiDAR data by Fanos, Ali Mutar, Pradhan, Biswajeet, Mansor, Shattri, Md Yusoff, Zainuddin, Abdullah, Ahmad Fikri, Jung, Hyung Sup

    Published 2019
    “…The availability of high-resolution laser scanning data and advanced machine learning algorithms has enabled an accurate potential rockfall source identification. …”
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    Article
  16. 16

    A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm by Ba-Quttayyan, Bakr Salim Abdullah

    Published 2024
    “…The developed framework, grounded in fault-based testing theory, comprises three key components: inputs, prioritization factors, and a prioritization algorithm. …”
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    Thesis
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    Optimising acoustic features for source mobile device identification using spectral analysis techniques / Mehdi Jahanirad by Mehdi , Jahanirad

    Published 2016
    “…Both models optimize acoustic features for source mobile device identification based on near-silent segments. The proposed feature sets along with selected feature extraction methods from the literature are analyzed and compared by using supervised learning techniques (i.e. support vector machines, nearest-neighbor, naïve Bayesian, neural network, logistic regression, and ensemble trees classifier), as well as unsupervised learning techniques (i.e. probabilistic-based and nearest-neighbor-based algorithms). …”
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    Thesis
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    A fuzzy multi-objective optimisation model of risk-based gas detector placement methodology for explosion protection in oil and gas facilities by Idris, A.M., Rusli, R., Nasif, M.S., Ramli, A.F., Lim, J.S.

    Published 2022
    “…Risk analysis is conducted to identify high risk areas that need flammable gas detectors protection, which is the input for the mathematical model. The proposed risk-based model was tested using a case study involving a natural gas liquids (NGL) recovery unit, and the results were compared to a published greedy algorithm (GA) formulation. …”
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    Article