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  1. 1
    Modified dynamic programming model with limited order picking capacity / Noraimi Azlin Mohd Nordin

    Modified dynamic programming model with limited order picking capacity / Noraimi Azlin Mohd Nordin by Noraimi Azlin , Mohd Nordin

    Published 2021
    “…Through this simulation model, it also helps to visualise the benefits that it may reduce the waiting time of customers that leads to increase in customers’ satisfaction. …”
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  2. 2
    Assessing the simulation performances of multiple model selection algorithm

    Assessing the simulation performances of multiple model selection algorithm by Yusof, Norhayati, Ismail, Suzilah, Tuan Muda, Tuan Zalizam

    Published 2015
    “…The capability of the algorithm in finding the true specification of multiple models is measured by the percentage of simulation outcomes.Overall results show that the algorithm has performed well for a model with two equations.The findings also indicated that the number of variables in the true models affect the algorithm performances. …”
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  3. 3
    Novel insight into the structural requirements of P70S6K inhibition using group-based quantitative structure activity relationship (GQSAR) (GQSAR)

    Novel insight into the structural requirements of P70S6K inhibition using group-based quantitative structure activity relationship (GQSAR) (GQSAR) by Abdullahi, Abubakar Danjuma, Mohammed Abdul Kader, Abdul Rahman, Abdul Samat, Nadia Hanis, Mohamed, Farahidah, Muhammad, Bala Yauri, Mohammed, Helaluddin Abul bashar, Aljarbou, Ahmed, Kasmuri, Abdul Razak

    Published 2014
    “…The dataset was then divided into a training set (n=40) and a test set (n=10) using a sphere exclusion algorithm. Multiple linear regressions coupled with simulated annealing or stepwise regression resulted in model A (r2=0.92) and model B (r2=0.87), respectively. …”
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  4. 4
    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 development of the simulation model consists of seven steps. The steps are problem definition, construct the simulation model, test and validate the model, design the simulation experiments, conduct the simulation experiments, evaluate the result and implement the result. …”
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  5. 5
    Incorporating the range-based method into GridSim for modeling task and resource heterogeneity

    Incorporating the range-based method into GridSim for modeling task and resource heterogeneity by Eng, Kailun, Muhammed, Abdullah, Mohamed, Mohamad Afendee, Hasan, Sazlinah

    Published 2017
    “…In this paper, we propose a new simulation model that incorporates the range-based method into GridSim for modeling and simulating heterogeneous tasks and resources in order to capture the inherent heterogeneity of Grid environments that later can be used by other researchers to test their algorithms.…”
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  6. 6
    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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  7. 7
    Development of Algorithm for QoS Model in Cloud Computing

    Development of Algorithm for QoS Model in Cloud Computing by Alfadli, Mohammed Abdullah, Noordin, Mohamad Fauzan, Billah, Md. Masum

    Published 2021
    “…After that, we will develop our new algorithm for the QoS Model. Then, we simulate the new enhanced algorithm and compare to other algorithms.…”
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  8. 8
    Simulation Model and Genetic Algorithm to Assembly Line Balancing

    Simulation Model and Genetic Algorithm to Assembly Line Balancing by Ali, A. J. Adham, Ahmad Nazif, Noor Kamar, Abdullah, Ibrahim, Sorooshian, Shahryar

    Published 2013
    “…The assembly line involves many famous problems that is unbalancing cycle time among the workstations. Simulation Model (SM) is one of the most useful modelling tool for the design of many types of systems. …”
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  9. 9
    Power Delivery Network Modeling And Simulation By Using Delaunay-Voronoi Triangulation And The Latency Insertion Method

    Power Delivery Network Modeling And Simulation By Using Delaunay-Voronoi Triangulation And The Latency Insertion Method by Chin, Wei Chun

    Published 2018
    “…The research is focused into the analysis of PDN by modeling and simulation of the power plane. In the project, power plane is modeled using Delaunay-Voronoi algorithm and for simulation, a fast transient simulation algorithm which is latency insertion method (LIM) is applied. …”
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  10. 10
    SURE-Autometrics algorithm for model selection in multiple equations

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

    Published 2016
    “…This automatic model selection algorithm is better than non-algorithm procedure which requires knowledge and extra time. …”
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  11. 11
    Modelling and simulation of hysteresis control algorithm for use in single phase ac-to-ac matrix converter / Seri Iryani Mohd Noor

    Modelling and simulation of hysteresis control algorithm for use in single phase ac-to-ac matrix converter / Seri Iryani Mohd Noor by Mohd Noor, Seri Iryani

    Published 2003
    “…This thesis is illustrated by developing computer simulation models of ac-to-ac single phase matrix converter (SPMC) using sinusoidal pulse width modulation (SPWM) technique and another algorithm i.e hysteresis control technique. …”
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  12. 12
    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems

    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

    Published 2014
    “…The results showed that the parallel algorithms for EHD simulations may provide 4 to 5 times more speedup over sequential algorithm for large grid sizes. …”
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  13. 13
    A simulation tool to evaluate the usability of agent centric Resource-Event-Agent (REA) database modeling methodology: The development of revenue cycle in accounting information system

    A simulation tool to evaluate the usability of agent centric Resource-Event-Agent (REA) database modeling methodology: The development of revenue cycle in accounting information sy... by Ming L.L.

    Published 2023
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  14. 14
    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…”
    Conference Paper
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  15. 15
    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
    “…Key parameters for dynamic processes of different domains were formulated for the construction of self-adaptive simulation algorithms and modelling. Self-adaptive simulation algorithms were formulated to enable the model’s adaptive capability. …”
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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
    Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance

    Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Koting, Suhana, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

    Published 2019
    “…This study attempts to integrate a forecasting model for reservoir inflow and evaporation with the operation rules generated from optimization models during the simulation procedure. …”
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  18. 18
    Utilization of canny and velocity bunching algorithms for modelling shoreline change

    Utilization of canny and velocity bunching algorithms for modelling shoreline change by Marghany, Maged, Hashim, Mazlan

    Published 2006
    “…There is significant relationship between shoreline change rate estimated using Canny algorithm and ones modeled using velocity bunching model. …”
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  19. 19
    Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm

    Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm by Nur Azulia, Kamarudin

    Published 2019
    “…In conclusion, SURE(IFGLS)-Autometrics and SURE(EM)-Autometrics can be used as models selection algorithms. Additionally, both algorithms are suitable in improving performance of automated models selection procedures. …”
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  20. 20
    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 simulation results showed that the developed GA-Taguchi ANN model could reduce the maximum prediction error below 10. …”
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