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  1. 1
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…The simulation is implemented with iFogSim and java programming language. …”
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  2. 2
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    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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  3. 3
    Ant colony optimization algorithm for load balancing in grid computing

    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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  4. 4
    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT

    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. …”
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  5. 5
    Observer-based fault detection with fuzzy variable gains and its application to industrial servo system

    Observer-based fault detection with fuzzy variable gains and its application to industrial servo system by Eissa, Magdy Abdullah, Sali, Aduwati, Hassan, Mohd Khair, Bassiuny, A. M., Darwish, Rania R.

    Published 2020
    “…The proposed fault detection algorithm employs a fuzzy logic-based approach with the objective of finding the appropriate observer gains that could cope with the different working conditions. …”
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  6. 6
    Comparing seabed roughness result from QPS fledermaus software, benthic trrain modeler [BTM] and developed model derived FRM slope variability algorithm for hard coral reef detection / Nur Asikin Mohd Sayud

    Comparing seabed roughness result from QPS fledermaus software, benthic trrain modeler [BTM] and developed model derived FRM slope variability algorithm for hard coral reef detecti... by Mohd Sayud, Nur Asikin

    Published 2018
    “…In this study, several models has been created which are from QPS Fledermaus model, BTM model and Slope Variability model. Slope variability model is an algorithm that is being used for detecting terrain roughness. …”
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  7. 7
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    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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  8. 8
    Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data

    Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data by Baba, Ishaq Abdullahi

    Published 2022
    “…The proposed algorithm has been applied to detect outliers in the high dimensional data. …”
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  9. 9
    Features selection for intrusion detection system using hybridize PSO-SVM

    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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  10. 10
    Minimization of Test Cases and Fault Detection Effectiveness Improvement through Modified Reduction with Selective Redundancy Algorithm

    Minimization of Test Cases and Fault Detection Effectiveness Improvement through Modified Reduction with Selective Redundancy Algorithm by Nikfal, Shima

    Published 2007
    “…Then the algorithm gathers all the test cases based on the definition occurrence and def-use pair if they cover same definition occurrence of one variable but they don’t cover def-use pair of the same variable. …”
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  11. 11
    Resource management in grid computing using ant colony optimization

    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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  12. 12
    Fault diagnostic algorithm for precut fractionation column

    Fault diagnostic algorithm for precut fractionation column by Heng, H. Y., Ali, Mohamad Wijayanuddin, Kamsah, Mohd. Zaki

    Published 2004
    “…Hazard and Operability Study (HAZOP) is used to support the diagnosis task. The algorithm has been successful in detecting the deviations of each variable by testing the data set. …”
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  13. 13
    Potential norms detection in social agent societies

    Potential norms detection in social agent societies by Mahmoud M.A., Mustapha A., Ahmad M.S., Ahmad A., Yusoff M.Z.M., Hamid N.H.A.

    Published 2023
    “…In this paper, we propose a norms mining algorithm that detects a domain's potential norms, which we called the Potential Norms Mining Algorithm (PNMA). …”
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  14. 14
    Artificial immune system based on real valued negative selection algorithms for anomaly detection

    Artificial immune system based on real valued negative selection algorithms for anomaly detection by Khairi, Rihab Salah

    Published 2015
    “…With respect to all the algorithms, V-Detector proved to be superior and surpassed all other algorithms based on performance and execution time.…”
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  15. 15
    Algorithm enhancement for host-based intrusion detection system using discriminant analysis

    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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  16. 16
    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter

    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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  17. 17
    Building norms-adaptable agents from Potential Norms Detection Technique (PNDT)

    Building norms-adaptable agents from Potential Norms Detection Technique (PNDT) by Mahmoud M.A., Ahmad M.S., Ahmad A., Mustapha A., Yusoff M.Z.M., Hamid N.H.A.

    Published 2023
    “…This technique enables an agent to update its norms even in the absence of sanctions from a third-party enforcement authority as found in some work, which entail sanctions by a third-party to detect and identify the norms. The PNDT consists of five components: agent's belief base; observation process; Potential Norms Mining Algorithm (PNMA) to detect the potential norms and identify the normative protocol; verification process, which verifies the detected potential norms; and updating process, which updates the agent's belief base with new normative protocol. …”
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  18. 18
    Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC)

    Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC) by Ibrahim, Kamarul 'Asri, Ahmad, Arshad, Ali, Mohamad Wijayanuddin, Mak, Weng Yee

    Published 2006
    “…Results showed that the developed FDD algorithm successfully detect and diagnosed the pre-designed faults. …”
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  19. 19
    Shape-based Road Sign Detection and Recognition for Embedded Application Using MATLAB

    Shape-based Road Sign Detection and Recognition for Embedded Application Using MATLAB by Md Sallah, Siti Sarah, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

    Published 2010
    “…The algorithm is based on the Hough transform method to detect lines in order to identify and determine the shape of the road sign. …”
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  20. 20
    Building norms-adaptable agents from Potential Norms Detection Technique (PNDT)

    Building norms-adaptable agents from Potential Norms Detection Technique (PNDT) by Mahmoud, Moamin Ahmed, Ahmad, Mohd Sharifuddin, Ahmad, Azhana, Mustapha, Aida, Mohd Yusoff, Mohd Zaliman, Abdul Hamid, Nurzeatul Hamimah

    Published 2013
    “…This technique enables an agent to update its norms even in the absence of sanctions from a third-party enforcement authority as found in some work, which entail sanctions by a third-party to detect and identify the norms. The PNDT consists of five components: agent’s belief base; observation process; Potential Norms Mining Algorithm (PNMA) to detect the potential norms and identify the normative protocol; verification process, which verifies the detected potential norms; and updating process, which updates the agent’s belief base with new normative protocol. …”
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