Search Results - (( processes simulation model algorithm ) OR ( java application learning algorithm ))

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  1. 1
    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
    “…Features selection process can be considered a problem of global combinatorial optimization in machine learning. …”
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  2. 2
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
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  3. 3
    A Self-Adaptive Agent-Based Dynamic Processes Simulation Modelling Framework

    A Self-Adaptive Agent-Based Dynamic Processes Simulation Modelling Framework by Loo Y.L., Ahmad A., Mustapha A., Mostafa S.A.

    Published 2023
    “…Adaptive algorithms; Agent based simulation; Agent-based simulation framework; Different domains; Domain specific; Dynamic process; Dynamic process simulation; Self-adaptive; Simulation framework; Simulation model; Simulation platform…”
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  4. 4
    A self-adaptive agent-based simulation modelling framework for dynamic processes

    A self-adaptive agent-based simulation modelling framework for dynamic processes by Ling, Loo Yim, Dr.

    Published 2023
    “…Agent-based simulation (ABS) modelling had been a prevalent approach for simulation of dynamic processes of various domains. …”
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  5. 5
    Process Planning Optimization In Reconfigurable Manufacturing Systems

    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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  6. 6
    Optimization of Prediction Error in CO2 Laser Cutting process by Taguchi Artificial Neural Network Hybrid with Genetic algorithm

    Optimization of Prediction Error in CO2 Laser Cutting process by Taguchi Artificial Neural Network Hybrid with Genetic algorithm by Nukman, Y., Hassan, M.A., Harizam, M.Z.

    Published 2013
    “…The model has significant benefits in application to fabrication processes.…”
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  7. 7
    Process fault detection and diagnosis using Boolean representation on fatty acid fractionation column

    Process fault detection and diagnosis using Boolean representation on fatty acid fractionation column by Othman, M. R., Ali, Mohamad Wijayanuddin, Kamsah, Mohd. Zaki

    Published 2003
    “…The algorithm utilizes process simulator to develop plant model in order to conduct sensitivity analysis and provide dynamic data on selected fault. …”
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  8. 8
    Modelling and environmental assessment of heterogeneous catalysis biodiesel process using war algorithm

    Modelling and environmental assessment of heterogeneous catalysis biodiesel process using war algorithm by As Eleyana, Ali

    Published 2013
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  9. 9
    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments

    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments by Chiang, A., Baba, M.S.

    Published 2006
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  10. 10
    Artificial Bee Colony algorithm in estimating kinetic parameters for yeast fermentation pathway

    Artificial Bee Colony algorithm in estimating kinetic parameters for yeast fermentation pathway by Ahmad Muhaimin, Ismail, Muhammad Akmal, Remli, Yee Wen, Choon, Nurul Athirah, Nasarudin, Norsyahidatul Nazirah, Ismail, Mohd Arfian, Ismail, Mohd Saberi, Mohamad

    Published 2023
    “…Analyzing metabolic pathways in systems biology requires accurate kinetic parameters that represent the simulated in vivo processes. Simulation of the fermentation pathway in the Saccharomyces cerevisiae kinetic model help saves much time in the optimization process. …”
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  11. 11
    A Model for Evaluation of Cryptography Algorithm on UUM Portal

    A Model for Evaluation of Cryptography Algorithm on UUM Portal by Norliana, Abdul Majid

    Published 2004
    “…The methodology used in this study begun with problem identification, requirement identification, analysed the model process and design the simulation model. The simulation model was developed using Active Server Page, JavaScript and SQL 7.0 as database. …”
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  12. 12
    Development of novel algorithm features in the modelling of cyclic processes

    Development of novel algorithm features in the modelling of cyclic processes by Choong, Thomas S.Y., Paterson, William R., Scott, David M.

    Published 2002
    “…We present two novel algorithm features for the transient simulation of cyclic processes that exhibit cyclic steady state (CSS). …”
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  13. 13
    Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage

    Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

    Published 2010
    “…Relative mass release of the leakage is introduced as the input for the simulation model and the data from the simulation model is taken at real time (on-line) to feed into the recursive algorithms. …”
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  14. 14
    Ensemble dual recursive learning algorithms for identifying flow with leakage

    Ensemble dual recursive learning algorithms for identifying flow with leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

    Published 2010
    “…Relative mass release of the leakage is introduced as the input for the simulation model and the data from the simulation model is taken at real time (on-line) to feed into the recursive algorithms. …”
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  15. 15
    Estimation in spot welding parameters using genetic algorithm

    Estimation in spot welding parameters using genetic algorithm by Lukman, Hafizi

    Published 2007
    “…In this study, parameter of spot welding estimate using computer simulation. System identification is the field of modeling a system from experiment or simulation data. …”
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  16. 16
    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models

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

    Published 2017
    “…Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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  17. 17
    Neural network based model predictive control for a steel pickling process

    Neural network based model predictive control for a steel pickling process by Kittisupakorn, P., Thitiyasook, P., Hussain, Mohd Azlan, Daosud, W.

    Published 2009
    “…The proposed algorithm is tested for control of a steel pickling process in several cases in simulation such as for set point tracking, disturbance, model mismatch and presence of noise. …”
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  18. 18
    SURE-Autometrics algorithm for model selection in multiple equations

    SURE-Autometrics algorithm for model selection in multiple equations by Norhayati, Yusof

    Published 2016
    “…Meanwhile, practitioners who are usually non-experts and lack of statistical knowledge will face difficulties during the modelling process. Hence, algorithm with a step by step guidance is beneficial in model building, testing and selection. …”
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  19. 19
    Recursive least square and fuzzy modelling using genetic algorithm for process control application

    Recursive least square and fuzzy modelling using genetic algorithm for process control application by Abdul Rahman, Ribhan Zafira, Yusof, Rubiyah, Khalid, Marzuki

    Published 2007
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  20. 20
    An Educational Tool Aimed at Learning Metaheuristics

    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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