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  1. 1

    Sentiment analysis on COVID-19 outbreak using PSO-SVM / Amir Danial Shahrul Sazali by Shahrul Sazali, Amir Danial

    Published 2024
    “…The created model achieves 73% accuracy in predicting sentiment of tweets when using a Linear SVM kernel with 70:30 percentage split ratio. The project is set to be improved by using a well-constructed SVM algorithm that can handle large data very well, using a more powerful hardware and unlimiting the language use to train the PSO-SVM.…”
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    Thesis
  2. 2

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This algorithm is used to extract important points from a lengthy document, by which it classifies each word in the document under its relevant category and constructs the structure of the summary with reference to the categorized words. …”
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    Final Year Project
  3. 3

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This algorithm is used to extract important points from a lengthy document, by which it classifies each word in the document under its relevant category and constructs the structure of the summary with reference to the categorized words. …”
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    Final Year Project
  4. 4

    An Arabic hadith text classification model using convolutional neural network and support vector machine / Mohd Irwan Mazlin by Mazlin, Mohd Irwan

    Published 2022
    “…Second, parameter tuning is conducted to find the best parameter for CNN-SVM. Third, the model (CNN-SVM, CNN and SVM) is monitored to see if their performance predicts unseen data. …”
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    Thesis
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    Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management by almahameed, Bader aldeen, Bisharah, Majdi

    Published 2024
    “…This study examines the utilization of different Machine Learning algorithms, such as Linear Regression, Decision Trees, Support Vector Machines (SVM), Gradient Boosting, Random Forest, K-Nearest Neighbors (KNN), Convolutional Neural Network (CNN) Regression, and Particle Swarm Optimization (PSO), in the domain of predictive modeling and cost optimization in the field of construction project management. …”
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    Article
  7. 7

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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    Thesis
  8. 8

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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    Monograph
  9. 9

    Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin by Mat Yasin, Zuhaila

    Published 2014
    “…To enhance the robustness of the algorithm, the QIEP technique is constructed based on multiobjective model in which the multiobjective functions consist of reducing power losses, increasing maximum loadability and cost minimisation. …”
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    Thesis
  10. 10

    Automated recognition of Ficus deltoidea using ant colony optimization technique by Ishak, Asnor Juraiza, Che Soh, Azura, Marhaban, Mohammad Hamiruce, Khamis, Shamsul, Ghasab, Mohammad Ali Jan

    Published 2013
    “…This paper presents innovative method to improve the accuracy of classification as well the efficiency, such that irrelevant features that make computational complexity are ignored by feature subset selection that is proposed by means of ant colony optimization algorithm (ACO). At first, through image processing specified features are extracted from the Ficus deltoidea leaves such as vein, morphology and texture features and they construct a search space to be chosen for the optimal subset features that is selected by ACO algorithm as support vector machine (SVM) classify them. …”
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    Conference or Workshop Item
  11. 11

    GA optimization-based BRB AI reasoning algorithm for determining the factors affecting customer churn for operators by Kun, Liu, Alli, Hassan, Abd Rahman, Khairul Aidil Azlin

    Published 2024
    “…Therefore, in this paper, a belief rule base (BRB) artificial intelligence inference algorithm based on GA optimization to determine the factors affecting customer churn for operators proposed. …”
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    Article
  12. 12

    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

    Published 2023
    “…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
    Review
  13. 13

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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    Thesis
  14. 14

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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    Thesis
  15. 15

    Efficient gear fault feature selection based on moth‑flame optimisation in discrete wavelet packet analysis domain by Ong, Pauline, Tieh, Tony Hieng Cai, Lai, Kee Huong, Lee, Woon Kiow, Ismon, Maznan

    Published 2019
    “…First, the vibration signals of gear with different fault conditions were decomposed by a fourth-level discrete wavelet packet transform, and the statistical features at all constructed nodes were derived. Second, the MFO algorithm was utilised to select the optimal discriminative features. …”
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    Article
  16. 16

    Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2011
    “…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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    Monograph
  17. 17

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

    Published 2004
    “…Alan Fan et aI., [2] use Support Vector Machine (SVM) to stock market prediction. The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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    Article
  18. 18

    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter by Azhar, Nur Huwaina

    Published 2019
    “…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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    Thesis
  19. 19

    Optimization of COCOMO model using particle swarm optimization by Zakaria, Noor Azura, Ismail, Amelia Ritahani, Zainal Abidin, Nadzurah, Mohd Khalid, Nur Hidayah, Yakath Ali, Afrujaan

    Published 2021
    “…In this paper, Particle Swarm Optimization (PSO) is proposed as a metaheuristics optimization method to hybrid with three traditional state-of-art techniques such as Support Vector Machine (SVM), LinearRegression (LR), and Random Forest (RF) for optimizing the parameters of COCOMO models. …”
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    Article
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