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  1. 1
    Path Planning and Control of Mobile Robot in Road Environments using Sensor Fusion and Active Force Control

    Path Planning and Control of Mobile Robot in Road Environments using Sensor Fusion and Active Force Control by Ali, Mohammed A. H., Mailah, Musa

    Published 2018
    “…With such an algorithm, the robot is able to localize itself within the road environment and find a collision free-path starting from a pre-defined start position to a goal point using a novel approach called laser simulator (LS). …”
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  2. 2
    Real time nonlinear filtered-x lms algorithm for active noise control

    Real time nonlinear filtered-x lms algorithm for active noise control by Sahib, Mouayad Abdulredha

    Published 2012
    “…Subsequently, the THF modelling scheme can be incorporated into an established real time NLFXLMS algorithm termed THF-NLFXLMS algorithm. The developed THF-NLFXLMS algorithm is tested by means of simulation and implemented experimentally using FPGA-based real time controller for a nonlinear ANC application. …”
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  3. 3
    Loudspeaker nonlinearity compensation with inverse tangent hyperbolic function-based predistorter for active noise control

    Loudspeaker nonlinearity compensation with inverse tangent hyperbolic function-based predistorter for active noise control by Sahib, Mouayad Abdulredha, Raja Ahmad, Raja Mohd Kamil

    Published 2014
    “…Simulation results show that using the proposed PD along with the FXLMS algorithm increase the noise reduction performance significantly. …”
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  4. 4
    Mobile Crowd Steering Evacuation Model via Agent Based Simulation by Applying the Social Force Model

    Mobile Crowd Steering Evacuation Model via Agent Based Simulation by Applying the Social Force Model by Norhaida, Binti Hussain, Wai Shiang, Cheah, Wai Loke, Seng

    Published 2025
    “…The context manager, path planning, and movement module of the original SFM were used to create the simulation model. …”
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  5. 5
    A Continuous Overlay Path Probing Algorithm For Overlay Networks

    A Continuous Overlay Path Probing Algorithm For Overlay Networks by Feily, Maryam

    Published 2013
    “…The primary idea is to perform active measurements using the applications’ packets instead of using extra probe packets. …”
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  6. 6
    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
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  7. 7
    Nonlinear FXLMS algorithm for active noise control systems with saturation nonlinearity

    Nonlinear FXLMS algorithm for active noise control systems with saturation nonlinearity by Sahib, Mouayad A., Raja Ahmad, Raja Mohd Kamil, Marhaban, Mohammad Hamiruce

    Published 2012
    “…In active noise control (ANC) applications, the saturation effect of the loudspeaker in the secondary path is considered as the most serious problem that could degrade performance of standard filtered-x least mean square (FXLMS) control algorithm. …”
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  8. 8
    An improved algorithm in test case generation from UML activity diagram using activity path

    An improved algorithm in test case generation from UML activity diagram using activity path by Hashim, Nor Laily, Salman, Yasir D.

    Published 2011
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  9. 9
    A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application

    A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application by Zainal Abidin, Zulkifli

    Published 2011
    “…The optimal simulation parameters can be used for the real application. …”
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  10. 10
    Nonlinear adaptive algorithm for active noise control with loudspeaker nonlinearity

    Nonlinear adaptive algorithm for active noise control with loudspeaker nonlinearity by Dehkordi, Sepehr Ghasemi

    Published 2014
    “…The proposed THF-NLFXLMS algorithm models the Wiener secondary path and applies the estimated degree of nonlinearity of the nonlinear secondary path in the control algorithm design. …”
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  11. 11
    All-pass filtered x least mean square algorithm for narrowband active noise control

    All-pass filtered x least mean square algorithm for narrowband active noise control by Mondal (Das), Kuheli, Das, Saurav, Abu, Aminudin, Hamada, Nozomu, Toh, Hoong Thiam, Das, Saikat, Faris, Waleed Fekry

    Published 2018
    “…Most available ANC uses the secondary path modelling including filtered x least mean square (FxLMS) algorithm. …”
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  12. 12
    An application of Floyd-Warshall Algortihm in finding shortest path of order picker in warehouse / Saidatul Aisyah Roslan, Siti Norhakimah Mohd Yatim and Siti Sarah Sulaiman

    An application of Floyd-Warshall Algortihm in finding shortest path of order picker in warehouse / Saidatul Aisyah Roslan, Siti Norhakimah Mohd Yatim and Siti Sarah Sulaiman by Roslan, Saidatul Aisyah, Mohd Yatim, Siti Norhakimah, Sulaiman, Siti Sarah

    Published 2019
    “…For the result, shortest path for the order pickers in iterations. The algorithm used can help the order picker to have the shortest path, but it have no direct path. …”
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  13. 13
    Optimization of turning parameters using genetic algorithm method

    Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

    Published 2008
    “…The simulation based on Genetic Algorithm are successful develop and the optimum parameters values are obtained from the simulation.…”
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  14. 14
    PSAT : a pairwise test data generation tool based on simulated annealing algorithm

    PSAT : a pairwise test data generation tool based on simulated annealing algorithm by Goh, Ghee Hau

    Published 2015
    “…This research is about the research on developing a Pairwise Test Data Generation Tool based on Simulated Annealing (SA) algorithm which named as PSAT. …”
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  15. 15
    Optimization of milling parameters using ant colony optimization

    Optimization of milling parameters using ant colony optimization by Mohd Saupi, Mohd Sauki

    Published 2008
    “…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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  16. 16
    The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed

    The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Ahmad A., Abdullah F., Ahmad W.S.H.M.W.

    Published 2024
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  17. 17
    An improved narrowband active noise control system without secondary path modelling based on the time domain

    An improved narrowband active noise control system without secondary path modelling based on the time domain by Mondal, Kuheli, Das, Saurav, Hamada, Nozomu, Haji Abu, Aminudin, Das, Saikat, Faris, Waleed Fekry, Toh, Hoong Thiam, Ahmad, Akij

    Published 2019
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  18. 18
    Parameter-Less Simulated Kalman Filter

    Parameter-Less Simulated Kalman Filter by Nor Hidayati, Abdul Aziz, Zuwairie, Ibrahim, Nor Azlina, Ab. Aziz, Saifudin, Razali

    Published 2017
    “…Simulated Kalman Filter (SKF) algorithm is a new population-based metaheuristic optimization algorithm. …”
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  19. 19
    Optimum Time-Cost Trade-Off Strategies on Critical Path Method for Project Management

    Optimum Time-Cost Trade-Off Strategies on Critical Path Method for Project Management by Khalaf, Wakas S.

    Published 2010
    “…When critical activity is stretched and the shortest possible of project completion is extended, other paths may also become noncritical, therefore, the noncritical activities can be stretched again until all the slack in the different noncritical paths is used up. …”
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  20. 20
    GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE

    GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE by MOHAMMED SHARIFF, NUR ATIQAH

    Published 2020
    “…The behavior of Genetic Algorithm (GA) where it generates and evolves the parameters towards a high-quality solution gives an advantage in obtaining ideal combination of parameters to fit in with the simulation. …”
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