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  1. 1
    A generalized laser simulator algorithm for optimal path planning in constraints environment

    A generalized laser simulator algorithm for optimal path planning in constraints environment by Aisha, Muhammad

    Published 2022
    “…The results demonstrated that the proposed method could generate an optimal collision-free path. Moreover, the proposed algorithm result are compared to some common algorithms such as the A* algorithm, Probabilistic Road Map, RRT, Bi-directional RRT, and Laser Simulator algorithm to demonstrate its effectiveness. …”
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  2. 2
    A generalized laser simulator algorithm for mobile robot path planning with obstacle avoidance

    A generalized laser simulator algorithm for mobile robot path planning with obstacle avoidance by Muhammad, Aisha, Ali, Mohammed A.H., Turaev, Sherzod, Abdulghafor, Rawad Abdulkhaleq Abdulmolla, Shanono, Ibrahim Haruna, Alzaid, Zaid, Alruban, Abdulrahman, Alabdan, Rana, Dutta, Ashit Kumar, Almotairi, Sultan

    Published 2022
    “…An optimal path between the start and target point is found by forming a wave of points in all directions towards the target position considering target minimum and border maximum distance principles. …”
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  3. 3
    Novel algorithm for mobile robot path planning in constrained environment

    Novel algorithm for mobile robot path planning in constrained environment by Muhammad, Aisha, Ali, Mohammed A. H., Turaev, Sherzod, Shanono, Ibrahim Haruna, Hujainah, Fadhl, Mohd Zubir, Mohd Nashrul, Faiz, Muhammad Khairi, Mohd Faizal, Erma Rahayu, Abdulghafor, Rawad Abdulkhaleq Abdulmolla

    Published 2021
    “…The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. …”
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  4. 4
    Novel algorithm for mobile robot path planning in constrained environment

    Novel algorithm for mobile robot path planning in constrained environment by Aisha, Muhammad, Ali, Mohammed A. H., Turaev, Sherzod, Shanono, Ibrahim Haruna, Hujainah, Fadhl, Mohd Nashrul, Mohd Zubir, Muhammad Khairi Faiz, ., Erma Rahayu, Mohd Faizal, Abdulghafor, Rawad

    Published 2022
    “…The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. …”
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  5. 5
    Novel algorithm for mobile robot path planning in constrained environment

    Novel algorithm for mobile robot path planning in constrained environment by Muhammad, Aisha, Ali, Mohammed A. H., Turaev, Sherzod, Shanono, Ibrahim Haruna, Hujainah, Fadhl, Mohd Nashrul, Mohd Zubir, Muhammad Khairi, Faiz, Erma Rahayu, Mohd Faizal, Abdulghafor, Rawad

    Published 2022
    “…The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. …”
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  6. 6
    Development of a State-Space Observer for Active Noise Control Systems

    Development of a State-Space Observer for Active Noise Control Systems by Muhssin, Mazin T.

    Published 2009
    “…The secondary path of the ANC system is modeled by using the LMS algorithm to complete the design of the Filtered-X Least Mean Square (FXLMS) controller. …”
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  7. 7
    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing

    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

    Published 2015
    “…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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  8. 8
    Levy slime mould algorithm for solving numerical and engineering optimization problems

    Levy slime mould algorithm for solving numerical and engineering optimization problems by J. J., Jui, M. A., Ahmad, M. I. M., Rashid

    Published 2022
    “…The proposed Levy Slime Mould Algorithm (LSMA) is a novel metaheuristic algorithm that integrates the Levy distribution into a new metaheuristic called Slime Mould Algorithm (SMA) for solving numerical and engineering problems. …”
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  9. 9
    Efficient and scalable ant colony optimization based WSN routing protocol for IoT

    Efficient and scalable ant colony optimization based WSN routing protocol for IoT by Sharmin, Afsah, Anwar, Farhat, Motakabber, S. M. A.

    Published 2020
    “…For this reason, many intelligent systems have been utilized to design routing algorithms to handle the network's dynamic state. In this paper, an ant colony optimization (ACO) based WSN routing algorithm for IoT has been proposed and analyzed to enhance scalability, to accommodate node mobility and to minimize initialization delay for time critical applications in the context of IoT to find the optimal path of data transmission, improvising efficient IoT communications. …”
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  10. 10
    Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms

    Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms by Hossain S.K.S., Ali S.S., Rushd S., Ayodele B.V., Cheng C.K.

    Published 2023
    “…Carbon nanotubes; Electrocatalysts; Electrooxidation; Forestry; Formic acid; Gaussian distribution; Learning algorithms; Palladium; Parameter estimation; Regression analysis; Support vector machines; Formic acid electrooxidation; Fuel cell application; Gaussian kernel functions; Gaussian process regression; Interaction effect; Machine learning algorithms; Performance; Process parameters; Regression trees; Support vector machine regressions; Sensitivity analysis…”
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  11. 11
    Development of an interactive learning tool for analysis of fast fourier transform from butterfly diagram

    Development of an interactive learning tool for analysis of fast fourier transform from butterfly diagram by Mohamad Syeihri Bin Mohamad Ismail

    Published 2023
    “…This project is to develop an interactive learning tool for the analysis of Fast Fourier Transform from the butterfly diagram. …”
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  12. 12
    Modeling the properties of terminal blend crumb rubber modified bitumen with crosslinking additives

    Modeling the properties of terminal blend crumb rubber modified bitumen with crosslinking additives by Jegatheesan N., Ibrahim M.R., Ahmed A.N., Koting S., El-Shafie A., Katman H.Y.B.

    Published 2025
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  13. 13
    Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining

    Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining by Sivarao, Subramonian

    Published 2009
    “…The researchers conducted the prediction of laser machining quality, namely surface roughness with seven significant parameters to obtain singleton output using machine learning techniques based on Quick Back Propagation Algorithm. …”
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  14. 14
    Autism Spectrum Disorder Classification Using Deep Learning

    Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

    Published 2021
    “…In the future, different types of deep learning algorithms need to be applied, and different datasets can be tested with different hyper-parameters to produce more accurate ASD classifications.…”
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  15. 15
    Machine learning model for performance prediction in mobile network management / Muhammad Hazim Wahid

    Machine learning model for performance prediction in mobile network management / Muhammad Hazim Wahid by Wahid, Muhammad Hazim

    Published 2022
    “…One of the major challenges when applying machine learning is to identify the best algorithm from a variety of algorithms to solve a problem. …”
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  16. 16
    Cybernetics approaches in intelligent systems for crops disease detection with the aid of IoT

    Cybernetics approaches in intelligent systems for crops disease detection with the aid of IoT by Rathinam R., Kasinathan P., Govindarajan U., Ramachandaramurthy V.K., Subramaniam U., Garrido S.

    Published 2023
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  17. 17
    Efficient relay placement algorithm using landscape aware routing (erpalar)

    Efficient relay placement algorithm using landscape aware routing (erpalar) by Onabajo, Olawale Olusegun

    Published 2011
    “…ERP ALAR was implemented in Matlab R2009a using Genetic Algorithm (GA) with multi-objectives. GA is an optimization algorithm that simulates natural selection process as found in nature. …”
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  18. 18
    A fast learning network with improved particle swarm optimization for intrusion detection system

    A fast learning network with improved particle swarm optimization for intrusion detection system by Ali, Mohammed Hasan

    Published 2019
    “…However, the internal power parameters (weight and basis) of FLN are initialized at random, causing the algorithm to be unstable. …”
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  19. 19
    A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites

    A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites by Din, Fakhrud

    Published 2019
    “…Unlike most existing meta-heuristic algorithms, and by virtue of being parameter-free, TLBO does not have any specific parameter controls. …”
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  20. 20
    Hyper-heuristic strategy for input-output-based interaction testing

    Hyper-heuristic strategy for input-output-based interaction testing by Din, Fakhrud, Kamal Zuhairi, Zamli

    Published 2022
    “…Classical test case design strategies, however, do not sufficiently include support for exploration of faults due to interaction between parameter values. New strategies known as t-way strategies (where t expresses interaction strength) have been developed for finding interaction faults. …”
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