Search Results - (( data classification based algorithm ) OR ( simulation optimization based algorithm ))

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  1. 1
    Ant colony optimization for rule induction with simulated annealing for terms selection

    Ant colony optimization for rule induction with simulated annealing for terms selection by Saian, Rizauddin, Ku-Mahamud, Ku Ruhana

    Published 2012
    “…This paper proposes a sequential covering based algorithm that uses an ant colony optimization algorithm to directly extract classification rules from the data set.The proposed algorithm uses a Simulated Annealing algorithm to optimize terms selection, while growing a rule.The proposed algorithm minimizes the problem of a low quality discovered rule by an ant in a colony, where the rule discovered by an ant is not the best quality rule, by optimizing the terms selection in rule construction. …”
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  2. 2
    An improved data classification framework based on fractional particle swarm optimization

    An improved data classification framework based on fractional particle swarm optimization by Sherwani, Fahad

    Published 2019
    “…Furthermore, the proposed MOFPSO algorithm is hybridized with Back-Propagation (BP), Elman Recurrent Neural Networks (RNN) and Levenberg-Marquardt (LM) Artificial Neural Networks (ANNs) to propose an enhanced data classification framework, especially for data classification applications. …”
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  3. 3
    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets

    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization. …”
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  4. 4
    WCBP: A new water cycle based back propagation algorithm for data classification

    WCBP: A new water cycle based back propagation algorithm for data classification by Mohd. Nawi, Nazri, Khan, Abdullah, Firdaus, Naim, M. Z., Rehman, Siming, Insaf Ali

    Published 2016
    “…The performance of the proposed Water Cycle based Back-Propagation (WCBP) algorithm is compared with the conventional BPNN, ABC-BP and ABC-LM algorithms on selected benchmark classification problems from UCI Machine Learning Repository. …”
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  5. 5
    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification

    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

    Published 2023
    “…Moreover, K-Nearest Neighbor (KNN) classifier was used to evaluate the effectiveness of the features identified by the proposed SCSO algorithm. The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
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  6. 6
    BAT-BP: A new BAT based back-propagation algorithm for efficient data classification

    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
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  7. 7
    Improved cuckoo search based neural network learning algorithms for data classification

    Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

    Published 2014
    “…On the other hand, LM algorithms which are derivative based algorithms still face a risk of getting stuck in local minima. …”
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  8. 8
    A new ant based rule extraction algorithm for web classification

    A new ant based rule extraction algorithm for web classification by Ku-Mahamud, Ku Ruhana, Saian, Rizauddin

    Published 2011
    “…Using Classifier-based attribute subset selection will reduce more attributes, but sacrifice the performance of the classifier.A hybrid ant colony optimization with simulated annealing algorithm to discover rules from data is proposed.The simulated annealing technique will minimize the problem of low quality discovered rule by an ant in a colony.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The rule set is arranged in decreasing order of generation.Thirteen data sets which consist of discrete and continuous data were used to evaluate the performance of the proposed algorithm in terms of accuracy, number of rules and number of terms in the rules.Experimental results obtained from the proposed algorithm are comparable to the results of the Ant-Miner algorithm in terms of rule accuracy but are better in terms of rule simplicity.…”
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  9. 9
    Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification

    Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification by Nawi, N.M., Khan, A., Rehman, M.Z., Chiroma, H., Herawan, T.

    Published 2015
    “…As a solution, nature inspired metaheuristic algorithms provide derivative-free solution to optimize complex problems. …”
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  10. 10
    A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets

    A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets by Mohd Razali, Muhamad Hasbullah, Saian, Rizauddin, Yap, Bee Wah, Ku-Mahamud, Ku Ruhana

    Published 2021
    “…This study proposed an enhanced algorithm called hellingerant-tree-miner (HATM) which is inspired by ant colony optimization (ACO) metaheuristic for imbalanced learning using decision tree classification algorithm. …”
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  11. 11
    Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)

    Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224) by Mahat, Nor Idayu, Engku Abu Bakar, Engku Muhammad Nazri, Zakaria, Ammar, Mohd Nazir, Mohd Amril Nurman, Misiran, Masnita

    “…This study developed an algorithm for statistical classification that enable ones to classify a future data to one of predetermined groups based on the measured data which facing two major threats; (i) multicollinearity among the measured variables and (ii) imbalanced groups. …”
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  12. 12
    Deep learning-based item classification for retail automation

    Deep learning-based item classification for retail automation by Ling, Ji Xiang

    Published 2025
    “…This project focuses on developing a deep learning-based system for retail item classification. The project aims to improve the efficiency and recognition accuracy in retail operations. …”
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  13. 13
    Neuro fuzzy classification and detection technique for bioinformatics problems

    Neuro fuzzy classification and detection technique for bioinformatics problems by Othman, Mohd. Fauzi, Moh, Thomas Shan Yau

    Published 2007
    “…A set diabetes data based on real diagnosis of patient was used.…”
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  14. 14
    The classification of wink-based eeg signals by means of transfer learning models

    The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

    Published 2021
    “…Whilst it was observed that the optimized k-NN model based on the aforesaid pipeline could achieve a classification accuracy of 100% for the training, validation, and tes t data. …”
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  15. 15
    Fault classification in smart distribution network using support vector machine

    Fault classification in smart distribution network using support vector machine by Chuan O.W., Ab Aziz N.F., Yasin Z.M., Salim N.A., Wahab N.A.

    Published 2023
    “…In this paper, a machine-learning algorithm known as Support Vector Machine (SVM) for fault type classification in distribution system has been developed. …”
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  16. 16
    The effect of pre-processing techniques and optimal parameters on BPNN for data classification

    The effect of pre-processing techniques and optimal parameters on BPNN for data classification by HUSSEIN, AMEER SALEH

    Published 2015
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  17. 17
    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…Then, this study aims to optimize the hyperparameters of the developed DNN model using the Arithmetic Optimization Algorithm (AOA) and, lastly, to evaluate the performance of the newly proposed deep learning model with Simulated Kalman Filter (SKF) algorithm in solving image encryption application. …”
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  18. 18
    An optimal under frequency load shedding scheme for islanded distribution network / Amalina Izzati Md Isa

    An optimal under frequency load shedding scheme for islanded distribution network / Amalina Izzati Md Isa by Md Isa, Amalina Izzati

    Published 2018
    “…Two new algorithms i.e., Load Classification based Fuzzy Logic (LCFL) and Binary Evolutionary Programming (BEP) are introduced in the module. …”
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  19. 19
    A new islanding detection technique based on passive parameter using a combination of artificial neural network and evolutionary programming algorithm / Hasmaini Mohamad …[et al.]

    A new islanding detection technique based on passive parameter using a combination of artificial neural network and evolutionary programming algorithm / Hasmaini Mohamad …[et al.]... by Mohamad, Hasmaini, Ab Salam, Aimie Nadia, Md Razali, Norhasniza, Salim, Nur Ashida, Mat Yasin, Zuhaila

    Published 2021
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  20. 20
    Malicious URL classification using artificial fish swarm optimization and deep learning

    Malicious URL classification using artificial fish swarm optimization and deep learning by Mustafa Hilal, Anwer, Hassan Abdalla Hashim, Aisha, G. Mohamed, Heba, K. Nour, Mohamed, M. Asiri, Mashael, M. Al-Sharafi, Ali, Othman, Mahmoud, Motwakel, Abdelwahed

    Published 2023
    “…To attain this, AFSADL-MURLC model initially carries out data preprocessing and makes use of glove-based word embedding technique. …”
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