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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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    Monograph
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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
    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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  6. 6
    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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  7. 7
    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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  8. 8
    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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  9. 9
    DC motor control using LQR algorithm

    DC motor control using LQR algorithm by Adezeno, Sagoli Olid

    Published 2008
    “…As in this project, the LQR controller will be develop in the PLC in order to control the DC motor running at optimum speed. …”
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    Undergraduates Project Papers
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  10. 10
    Extended bat algorithm for PID controller tuning of wheeled mobile robot and swarm robotics target searching strategy

    Extended bat algorithm for PID controller tuning of wheeled mobile robot and swarm robotics target searching strategy by Nur Aisyah Syafinaz, Suarin

    Published 2020
    “…Although PID controller is a traditional controller with simple architecture, tuning PID controller to the best gains in order to develop good performance system is difficult. …”
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  11. 11
    Liquid slosh suppression by implementing data-driven fractional order pid controller based on marine predators algorithm

    Liquid slosh suppression by implementing data-driven fractional order pid controller based on marine predators algorithm by Mohd Tumari, Mohd Zaidi Mohd, Mustapha, Nik Mohd Zaitul Akmal, Ahmad, Mohd Ashraf, Saat, Shahrizal, Ghazali, Mohd Riduwan

    Published 2023
    “…Thus, this research paper proposed the development of a data-driven fractional-order PID controller based on marine predators algorithm (MPA) for liquid slosh suppression system. …”
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    Conference or Workshop Item
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  12. 12
    Sixth Order Polynomial Model And Skyhook Algorithm Based Fuzzy Logic Control Of Magnetorheological Damper For Automotive Suspension System

    Sixth Order Polynomial Model And Skyhook Algorithm Based Fuzzy Logic Control Of Magnetorheological Damper For Automotive Suspension System by Ubaidillah, .

    Published 2010
    “…The results show that skyhook algorithm based fuzzy logic control gives better performances than its counterparts.…”
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  13. 13
    Research on nonlinear automation for first order delays system

    Research on nonlinear automation for first order delays system by Roshanzamir, Ali, Piltan, Farzin, Jahed, Arman, Namvarchi, Saman, Nazari, Iman, Sulaiman, Nasri

    Published 2015
    “…This work, proposes a developed method to design nonlinear based PID controller. …”
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  14. 14
    Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control

    Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control by Srazhidinov, Radik

    Published 2016
    “…Nonlinear FXLMS (NLFXLMS) control algorithm based on SEF has been previously developed to cancel the noise in environment with external factors that can cause nonlinearity. …”
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  15. 15
    Performance study of Reference Height Control Algorithm for Tripod Hopping Robot

    Performance study of Reference Height Control Algorithm for Tripod Hopping Robot by Anuar , Mohamed Kassim, Abas, Norafizah, Mohd Aras, Mohd Shahrieel, Ab Rashid, Mohd Zamzuri

    Published 2013
    “…As the result, the effectiveness of proposed reference height control algorithm in order to achieve the reference height is confirmed.…”
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  16. 16
    A novel softsign fractional-order controller optimized by an intelligent nature-inspired algorithm for magnetic levitation control

    A novel softsign fractional-order controller optimized by an intelligent nature-inspired algorithm for magnetic levitation control by Ahmad, Mohd Ashraf, Izci, Davut, Ekinci, Serdar, Mohd Tumari, Mohd Zaidi

    Published 2025
    “…This study presents a novel softsign-function-based fractional-order proportional–integral–derivative (softsign-FOPID) controller optimized using the fungal growth optimizer (FGO) for the stabilization and precise position control of an unstable magnetic ball suspension system. …”
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  17. 17
    Development of location-inventory model based on all-unit quantity discount policy

    Development of location-inventory model based on all-unit quantity discount policy by Firoozi, Zahra

    Published 2011
    “…Thus, this research has formulated and solved a joint location-inventory problem, while all-unit quantity discount is considered as the inventory policy of distribution network. In order to solve the model, two heuristics and one enumeration algorithm are developed. …”
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  18. 18
    PID TUNING OF DC MOTOR USING SWARM ITELLIGENCE ALGORITHM

    PID TUNING OF DC MOTOR USING SWARM ITELLIGENCE ALGORITHM by Hasdi Aimon, Arhimny

    Published 2012
    “…In order to evaluate the control performance, the three control parameters will be used to tune DC Motor simulated in MATLAB. …”
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    Final Year Project
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  19. 19
    DEVELOPMENT OF INTELLIGENT CONTROLLER FOR TRAFFIC LIGHTS WITH DYNAMIC PHASE ARRANGEMENT FOR SINGLE-ISOLATED INTERSECTIONS

    DEVELOPMENT OF INTELLIGENT CONTROLLER FOR TRAFFIC LIGHTS WITH DYNAMIC PHASE ARRANGEMENT FOR SINGLE-ISOLATED INTERSECTIONS by KAMAL ABBAS, MAYTHEM AL-ADILI

    Published 2014
    “…The first decision made by the controlling algorithm was the sequence priority. This algorithm expands the Djikestra's shortest path algorithm to choose the optimal dual-green-phase to be operated at a moment of time.…”
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  20. 20
    Optimization Of Sliding Mode Control Using Particle Swarm Algorithm For An Electro-Hydraulic Actuator System

    Optimization Of Sliding Mode Control Using Particle Swarm Algorithm For An Electro-Hydraulic Actuator System by Rozaimi, Ghazali

    Published 2016
    “…The dynamic parts of electro-hydraulic actuator(EHA) system are widely applied in the industrial field for the process that exposed to the motion control.In order to achieve accurate motion produced by these dynamic parts,an appropriate controller will be needed.However,the EHA system is well known to be nonlinear in nature.A great challenge is carried out in the EHA system modelling and the controller development due to its nonlinear characteristic and system complexity.An appropriate controller with proper controller parameters will be needed in order to maintain or enhance the performance of the utilized controller.This paper presents the optimization on the variables of sliding mode control (SMC) by using Particle Swarm Optimization (PSO) algorithm.The control scheme is established from the derived dynamic equation which stability is proven through Lyapunov theorem.From the obtained simulation results,it can be clearly inferred that the SMC controller variables tuning through PSO algorithm performed better compared with the conventional proportionalintegral-derivative (PID) controller.…”
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