Search Results - (( variable control optimization algorithm ) OR ( java application scheduling algorithm ))

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  1. 1

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…The CPU profiler of JavaTM VisualVM measures the number of invocations of scheduling event handlers (procedures) in each algorithm as well as the total time spent in all invocations of this handler. …”
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    Conference or Workshop Item
  2. 2

    A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

    Published 2014
    “…In this type of environment it is nearly impossible to prove the effectiveness of a scheduling algorithm. Hence the main objective of this study is to develop a desktop grid simulator toolkit for measuring and modeling scheduler algorithm performance. …”
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    Final Year Project
  3. 3

    Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

    Published 2006
    “…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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    Thesis
  4. 4

    Improving Class Timetabling using Genetic Algorithm by Qutishat, Ahmed Mohammed Ali

    Published 2006
    “…This paper reports the power fill techniques using GA in scheduling. Class timetabling problem is one of the applications in scheduling. …”
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    Thesis
  5. 5

    Examination timetabling using genetic algorithm case study: KUiTTHO by Mohd Salikon, Mohd Zaki

    Published 2005
    “…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
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    Thesis
  6. 6

    Study of nature inspired computing (NIC) technique for optimal reactive power dispatch problems by Sulaiman, Mohd Herwan

    Published 2017
    “…The proposed algorithms are tested on five different case studies which are IEEE 30-bus system with 13 control variables, IEEE 30-bus system with 19 control variables, IEEE 30-bus system with 25 control variables, IEEE 57-bus system with 25 control variables and IEEE 118-bus system with 77 control variables. …”
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    Research Report
  7. 7

    Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO by Mohd. Zaki, Mohd. Salikon

    Published 2005
    “…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
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    Thesis
  8. 8

    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
    “…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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    Article
  9. 9

    Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization by Nur Iffah, Mohamed Azmi

    Published 2014
    “…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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    Thesis
  10. 10
  11. 11

    Cuckoo search algorithm as an optimizer for optimal reactive power dispatch problems by M. H., Sulaiman, Zuriani, Mustaffa

    Published 2017
    “…This paper presents the application of Cuckoo Search Algorithm (CSA) in optimizing the control variables of power system operation in solving the optimal reactive power dispatch (ORPD) problem. …”
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    Conference or Workshop Item
  12. 12
  13. 13

    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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    Article
  14. 14

    Harmony search-based robust optimal controller with prior defined structure by Rafieishahemabadi, Ali

    Published 2013
    “…In this approach, a combination of interacting two levels HS optimization algorithm is presented. In the first level, a new method for analytical formulation of integral square error cost function based on controller variables is elaborated for performance evaluation purposes by the proposed optimization algorithm. …”
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    Thesis
  15. 15

    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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    Article
  16. 16

    Batch mode heuristic approaches for efficient task scheduling in grid computing system by Maipan-Uku, Jamilu Yahaya

    Published 2016
    “…Many algorithms have been implemented to solve the grid scheduling problem. …”
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    Thesis
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    A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification by Suihai, Chen, Chih How, Bong, Po Chan, Chiu

    Published 2024
    “…However, compared with the traditional risk control algorithm (logistic regression algorithm), CatBoost algorithm also needs to have the advantages of high efficiency, low algorithm complexity and strong interpretable ability. …”
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    Thesis
  19. 19

    On the optimal control of the steel annealing processes as a two-stage hybrid systems via PSO algorithms by Arumugam, M.S., Murthy, G.R., Loo, C.K.

    Published 2009
    “…The computation of optimal control variables for a two-stage steel annealing process which comprises of one or more furnaces is proposed in this paper. …”
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    Article
  20. 20

    Imposed weighting factor optimization method for torque ripple reduction of IM fed by indirect matrix converter with predictive control algorithm by Uddin, M., Mekhilef, Saad, Rivera, M., Rodriguez, J.

    Published 2015
    “…The conventional and introduced weighting factor optimization method in predictive control algorithm are validated through simulations and experimental validation in DS1104 R&D controller platform and show the potential control, tracking of variables with their respective references and consequently reduces the torque ripple.…”
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    Article