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  1. 1
    The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification

    The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification by Faizol, Bin Mohd Suria

    Published 2020
    “…Therefore, we conclude that the proposed BFOA-G is the best algorithm in the study, and PG approach is recommended for further development of BFOA as an IS algorithm.…”
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  2. 2
    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection

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

    Published 2022
    “…Experimental results of the EBGWO algorithm on the NSL-KDD dataset in terms of number of selected features and classification accuracy are superior to other benchmark optimisation algorithms. …”
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  3. 3
    A new standardisation and selection framework for real-time image dehazing algorithms from multi-foggy scenes based on fuzzy Delphi and hybrid multi-criteria decision analysis methods

    A new standardisation and selection framework for real-time image dehazing algorithms from multi-foggy scenes based on fuzzy Delphi and hybrid multi-criteria decision analysis meth... by Abdulkareem, Karrar Hameed, Arbaiy, Nureize, Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Alsalem, M. A., M. Salih, Mahmood

    Published 2020
    “…Given the rapid development of dehazing image algorithms, selecting the optimal algorithm based on multiple criteria is crucial in determining the efficiency of an algorithm. …”
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  4. 4
    Multi-Hop Selective Constructive Interference Flooding Protocol For Wireless Sensor Networks

    Multi-Hop Selective Constructive Interference Flooding Protocol For Wireless Sensor Networks by Alhalabi, Huda A. H.

    Published 2019
    “…MSCIF integrates three main algorithms: clustering algorithm, selection algorithm, and a synchronized flooding. …”
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  5. 5
    Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition

    Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition by Yahya, Anwar Ali, Mahmod, Ramlan, Ramli, Abd Rahman

    Published 2010
    “…In the second stage, the developed variable length genetic algorithm is used to select different sets of lexical cues to constitute the dynamic Bayesian networks' random variables. …”
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  6. 6
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  7. 7
    Efficient selective encryption schemes to secure video data and moving objects information for HEVC/H.265 using advanced encryption standard / Mohammed Ahmed Mohammed Saleh

    Efficient selective encryption schemes to secure video data and moving objects information for HEVC/H.265 using advanced encryption standard / Mohammed Ahmed Mohammed Saleh by Mohammed Saleh, Mohammed Ahmed

    Published 2016
    “…All of those encryption algorithms are classified as asymmetric and symmetric algorithms. …”
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  8. 8
    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network

    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

    Published 2014
    “…Second, the obtained results that included arrays of the top-ranked features were used as the initial population of a genetic algorithm to produce optimum arrays of features. Third, using a modified k-Nearest Neighbor method as well as an improved method of backpropagation neural networks, the classification process was advanced based on optimum arrays of the features selected by genetic algorithms. …”
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  9. 9
    Review of the research landscape of multi-criteria evaluation and bench- marking processes for many-objective optimisation methods: coherent taxonomy, challenges and recommended solution

    Review of the research landscape of multi-criteria evaluation and bench- marking processes for many-objective optimisation methods: coherent taxonomy, challenges and recommended so... by Mohammed, R. T., Yaakob, R., Zaidan, A. A., Sharef, N. M., Abdullah, R. H., Zaidan, B. B., Dawood, K. A.

    Published 2020
    “…Third, the development phase involves the creation of a decision matrix for MaOO selection on the basis of the integrated BWM and VIKOR method. …”
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  10. 10
    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.

    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

    Published 2020
    “…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
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    UMK Etheses
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  11. 11
    Development of intelligent evaluation system for product end-of-life selection strategy

    Development of intelligent evaluation system for product end-of-life selection strategy by Zakri, Ghazalli

    Published 2011
    “…This problem can be best resolved by promoting end-of-life (EOL) selection strategies. The main objective of this research is to develop an evaluation system for selecting EOL strategy specifically for remanufacturing. …”
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  12. 12
    Efficient genetic partitioning-around-medoid algorithm for clustering

    Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

    Published 2019
    “…This study utilizes genetic algorithms based upon the medoid rather than the mean as a centroid-selection schema to improve the clustering efficiency. …”
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  13. 13
    Web-Based Route Optimization System For Logistic Using Agglomerative Clustering And Genetic Algorithm

    Web-Based Route Optimization System For Logistic Using Agglomerative Clustering And Genetic Algorithm by Tan, Chee Kuan

    Published 2020
    “…In this project, evolutionary prototype methodology was selected to smooth the software development according to the scopes and also the requirements. …”
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    Final Year Project / Dissertation / Thesis
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  14. 14
    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh

    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

    Published 2015
    “…The performance of DE algorithm depends heavily on the selected mutation strategy and its associated control parameters. …”
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  15. 15
    Performance analysis of pair-wise error probability for 1/3 and 1/4 subcarrier mapping ICI-SC scheme in STFBC MIMO-OFDM system / Norhayati Abdullah

    Performance analysis of pair-wise error probability for 1/3 and 1/4 subcarrier mapping ICI-SC scheme in STFBC MIMO-OFDM system / Norhayati Abdullah by Abdullah, Norhayati

    Published 2015
    “…The simulation results expressively show that the one third method subcarrier mapping technique with Decision Feedback Equalizer (DFE) and adaptive algorithm can provide the best system performance compared to the existing subcarrier mapping methods .The results shows that by using the one-third subcarrier mapping scheme with an adaptive algorithm Normalised Least Means Square (NLMS), an efficient bandwidth can be achieved, ICI and ISI effects can be reduced with 24% of improvement compared to one-third subcarrier mapping Recursive Least Square (RLS) DFE in the MIMO-OFDM system.…”
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  16. 16
    Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network

    Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network by Mohd Hamdan, Eleena Yasmeen

    Published 2021
    “…To achieve those objectives, there were three main phases implemented in the network development framework; first, the determination of feature extraction using multiway principal component analysis (MPCA), second, the ANN model development and architecture selection for BOD and COD analysis, and third, the ANN architecture selection for WQI prediction model. …”
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    Monograph
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  17. 17
    Using genetic algorithms to optimise land use suitability

    Using genetic algorithms to optimise land use suitability by Pormanafi, Saeid

    Published 2012
    “…In this study, under environmentfriendliness objective, based on multi-agent genetic algorithms, was developed a geospatial model for the land use allocation. …”
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  18. 18
    Energy efficiency of the bitcoin mining hardware and related blockchain technology

    Energy efficiency of the bitcoin mining hardware and related blockchain technology by Noor Faiqah Izzati, Afandi

    Published 2018
    “…MATLAB is used in developing and validation the algorithm. Dataset was selected from open sources and applied in the proposed formula to evaluate and predict energy efficiency of bitcoin mining hardware. …”
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    Undergraduates Project Papers
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  19. 19
    Information Theoretic-based Feature Selection for Machine Learning

    Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

    Published 2018
    “…Thus, this thesis has developed and evaluated a filter based Information Theoretic-based Feature Selection (IFS) for machine learning. …”
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  20. 20
    Fuzzy clustering method and evaluation based on multi criteria decision making technique

    Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

    Published 2018
    “…For the third problem a modified of Kohonen Network (MKN) algorithm was proposed to select the initial centres of clusters. …”
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