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  1. 1
    Seed disperser ant algorithm for optimization / Chang Wen Liang

    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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  2. 2
    Class binarization with self-adaptive algorithm to improve human activity recognition

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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  3. 3
    Y-type Random 2-satisfiability In Discrete Hopfield Neural Network

    Y-type Random 2-satisfiability In Discrete Hopfield Neural Network by Guo, Yueling

    Published 2024
    “…During the retrieval phase, a new activation function and Swarm Mutation were proposed to ensure the diversity of the neuron states. The proposed algorithm and mutation mechanism showed optimal performances as compared to the existing algorithms. …”
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  4. 4
    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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  5. 5
    Classification with degree of importance of attributes for stock market data mining

    Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

    Published 2004
    “…The experimental results show that predictive FDT algorithm can generate a relatively optimal tree without much computation effort (comprehensibility), and WFPRs have a better predictive accuracy of stock market time series data. …”
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  6. 6
    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions

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

    Published 2018
    “…The second technique is to solve bi-objective functions by using the BOBAT algorithm. …”
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  7. 7
    Solving economic load dispatch problem using genetic algorithm method / Norliza Kamarulzaman

    Solving economic load dispatch problem using genetic algorithm method / Norliza Kamarulzaman by Kamarulzaman, Norliza

    Published 2009
    “…The determination of power system operation of data is based on the generation output and coefficients involved. …”
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  8. 8
    Hybridizing harmony search with local search based metaheuristic for solving curriculum based university course timetabling / Juliana Wahid

    Hybridizing harmony search with local search based metaheuristic for solving curriculum based university course timetabling / Juliana Wahid by Wahid, Juliana

    Published 2017
    “…Thus, this thesis proposed hybrid algorithms between HSA and local search based methods (simulated annealing (SA) and/or great deluge (GD)) to enhance the HSA performance for solving curriculum-based course timetabling (CBCTT) problem which is the variant of UCTP. …”
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  9. 9
    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems

    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems by Zulkifli, Munierah, Abd Rahmin, Nor Aliza, Wah, June Leong

    Published 2023
    “…SGD uses random or batch data sets to compute gradient in solving optimization problems. …”
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  10. 10
    Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud

    Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud by Shariff, S. Sarifah Radiah, Hud, Hady

    Published 2023
    “…The best algorithm will not be the same for all the data sets. …”
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  11. 11
    Heuristic-Based Ant Colony Optimization Algorithm For Protein Functional Module Detection In Protein Interaction Network

    Heuristic-Based Ant Colony Optimization Algorithm For Protein Functional Module Detection In Protein Interaction Network by SALLIM, JAMALUDIN

    Published 2017
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  12. 12
    Heuristic-Based Ant Colony Optimization Algorithm For Protein Functional Module Detection In Protein Interaction Network

    Heuristic-Based Ant Colony Optimization Algorithm For Protein Functional Module Detection In Protein Interaction Network by Sallim, Jamaludin

    Published 2017
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  13. 13
    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach

    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

    Published 2022
    “…Accuracy by using 80:20 ratio of training and test data gives result 98% of accurate training data, and 73% of test data are predicted with the proposed algorithm while 91 and 40% of the DNN models are predicted in training and test data.…”
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  14. 14
    Investigation of evolutionary multi-objective algorithms in solving view selection problem / Seyed Hamid Talebian

    Investigation of evolutionary multi-objective algorithms in solving view selection problem / Seyed Hamid Talebian by Talebian, Seyed Hamid

    Published 2013
    “…As a comparative study, the performance of the algorithms was evaluated based on various standard metrics. …”
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  15. 15
    An improved pheromone-based kohonen self-organising map in clustering and visualising balanced and imbalanced datasets

    An improved pheromone-based kohonen self-organising map in clustering and visualising balanced and imbalanced datasets by Azlin, Ahmad, Rubiyah, Yusof, Nor Saradatul Akmar, Zulkifli, Mohd Najib, Ismail

    Published 2021
    “…Therefore, this research proposed an improved pheromone- based PKSOM algorithm known as iPKSOM to solve the mentioned problem. …”
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  16. 16
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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  17. 17
    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection

    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

    Published 2020
    “…Many fields such as data science, data mining suffered from the rapid growth of data volume and high data dimensionality. …”
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  18. 18
    Weighted Sum-Dijkstra’s Algorithm in Best Path Identification based on Multiple Criteria

    Weighted Sum-Dijkstra’s Algorithm in Best Path Identification based on Multiple Criteria by Ting, Kien Hua, Noraini Abdullah

    Published 2018
    “…When come to large scale data problems, Maple software is used to solve it with ease.…”
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  19. 19
    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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  20. 20
    Solving curriculum based course timetabling by hybridizing local search based method within harmony search algorithm

    Solving curriculum based course timetabling by hybridizing local search based method within harmony search algorithm by Wahid, Juliana, Mohd Hussin, Naimah

    Published 2015
    “…The great deluge was applied either on the memory consideration operator, or random consideration operator or both operators together.In addition, several harmony memory consideration rates were applied on those setups. The algorithms of all setups were tested on curriculum-based data sets taken from the International Timetabling Competition, ITC2007. …”
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