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  1. 1
    Optimized clustering with modified K-means algorithm

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…In order to obtain the optimum number of clusters and at the same time could deal with correlated variables in huge data, modified k-means algorithm was proposed. …”
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  2. 2
    Efficient genetic partitioning-around-medoid algorithm for clustering

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

    Published 2019
    “…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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  3. 3
    Statistical performance of agglomerative hierarchical clustering technique via pairing of correlation-based distances and linkage methods

    Statistical performance of agglomerative hierarchical clustering technique via pairing of correlation-based distances and linkage methods by Nurshaziana, Mohamad Shamsuri

    Published 2025
    “…To validate the clustering model on real data, the Spearman-average algorithm was applied to cluster Juru river basin data based on five water quality parameters. …”
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  4. 4
    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals

    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

    Published 2020
    “…The third method is the hybridization of BPSO and Binary Differential Evolution, namely Binary Particle Swarm Optimization Differential Evolution (BPSODE). …”
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  5. 5
    Prediction of Machine Failure by Using Machine Learning Algorithm

    Prediction of Machine Failure by Using Machine Learning Algorithm by Fakhrurazi, Nur Amalina

    Published 2019
    “…Validation for the model is analyzed by using validation testing data and cross validation. …”
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  6. 6
    Seed disperser ant algorithm for optimization / Chang Wen Liang

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

    Published 2018
    “…In this research, we applied SDAA to solve the constrained engineering problems and introduce an efficient data clustering algorithm which is hybrid of K-means and SDAA. …”
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  7. 7
    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution

    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Ahmad Nazri, Azree Shahrel, Mohamed, Raihani, Abd Manaf, Syaifulnizam

    Published 2017
    “…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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  8. 8
    Differential evolution for neural networks learning enhancement

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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  9. 9
    Application of Optimization Methods for Solving Clustering and Classification Problems

    Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

    Published 2011
    “…Intuitively, samples within a valid cluster are more similar to each other than they are to a sample belonging to a different cluster. …”
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  10. 10
    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification

    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

    Published 2012
    “…This study is an attempt to design a method for an autonomous pattern classification and recognition system for emotion recognition. …”
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    Conference or Workshop Item
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  11. 11
    A New Co-Evolution Binary Particle Swarm Optimization With Multiple Inertia Weight Strategy For Feature Selection

    A New Co-Evolution Binary Particle Swarm Optimization With Multiple Inertia Weight Strategy For Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

    Published 2019
    “…To examine the effectiveness of proposed method, four recent and popular feature selection methods namely BPSO, genetic algorithm (GA), binary gravitational search algorithm (BGSA) and competitive binary grey wolf optimizer (CBGWO) are used in a performance comparison. …”
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  12. 12
    Email spam classification based on deep learning methods: A review

    Email spam classification based on deep learning methods: A review by Tusher, Ekramul Haque, Mohd Arfian, Ismail, Anis Farihan, Mat Raffei

    Published 2025
    “…Deep learning has become a potent collection of techniques for addressing intricate issues such as spam classification in recent times. A thorough literature evaluation is required to have a comprehensive overview of the current research on utilizing deep learning methods for email spam classification. …”
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  13. 13
    Artificial fish swarm optimization for multilayer network learning in classification problems

    Artificial fish swarm optimization for multilayer network learning in classification problems by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam

    Published 2012
    “…Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN.In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems.The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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  14. 14
    Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems

    Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2012
    “…Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN. …”
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  15. 15
    An improved method using fuzzy system based on hybrid boahs for phishing attack detection

    An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

    Published 2022
    “…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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  16. 16
    Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed

    Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

    Published 2012
    “…In conventional hard clustering approach, the number of clusters was determined by hierarchical clustering and two-step cluster analysis; then the sites were allocated to the appropriate cluster by k-means clustering method. …”
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  17. 17
    Centre based evolving clustering framework with extended mobility features for vehicular ad-hoc networks

    Centre based evolving clustering framework with extended mobility features for vehicular ad-hoc networks by Talib, Mohammed Saad

    Published 2021
    “…This framework uses an evolving data clustering algorithm by adopting the concept of grid granularity to capture the features of a cluster more efficiently. …”
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  18. 18
    Classification of Immunosignature Using Random Forests for Cancer Diagnosis

    Classification of Immunosignature Using Random Forests for Cancer Diagnosis by Zarzar, Mouayad, Razak, Eliza, Htike@Muhammad Yusof, Zaw Zaw, Yusof, Faridah

    Published 2015
    “…To attain this essential research purpose, a minimum set of genes that can assure higher performance in classification using data mining algorithms need to be detected. …”
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    Proceeding Paper
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  19. 19
    EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization

    EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization by Too, Jing Wei, Tee, Wei Hown, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

    Published 2019
    “…In order to measure the effectiveness of PBPSO, binary particle swarm optimization (BPSO), genetic algorithm (GA), modified binary tree growth algorithm (MBTGA), and binary differential evolution (BDE) were used for performance comparison. …”
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  20. 20
    3D surface roughness measurement for scaliness scoring of psoriasis lesions

    3D surface roughness measurement for scaliness scoring of psoriasis lesions by Ahmad Fadzil, M.H., Prakasa, E., Asirvadam, V.S., Nugroho, H., Affandi, A.M., Hussein, S.H.

    Published 2013
    “…The algorithm has been validated with an accuracy of 94.12. …”
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