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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
    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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  8. 8
    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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  9. 9
    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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  10. 10
    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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  11. 11
    Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data

    Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data by Amri, A’inur A’fifah, Ismail, Amelia Ritahani, Zarir, Abdullah Ahmad

    Published 2018
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  12. 12
    Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering

    Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

    Published 2024
    “…Although the swmcan algorithm solves the noise problem in multi-view data, its initial and final graphs are independent and cannot learn from each other. …”
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  13. 13
    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
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  14. 14
    Meta-heuristics and deep learning for energy applications: Review and open research challenges (2018?2023)

    Meta-heuristics and deep learning for energy applications: Review and open research challenges (2018?2023) by Hosseini E., Al-Ghaili A.M., Kadir D.H., Gunasekaran S.S., Ahmed A.N., Jamil N., Deveci M., Razali R.A.

    Published 2025
    “…This paper provides a comprehensive review spanning 2018 to 2023, examining the integration of meta-heuristic algorithms within deep learning frameworks for energy applications. …”
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  15. 15
    E4ML: Educational Tool for Machine Learning

    E4ML: Educational Tool for Machine Learning by Sainin, Mohd Shamrie, Siraj, Fadzilah

    Published 2003
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  16. 16
    Machine learning: tasks, modern day applications and challenges

    Machine learning: tasks, modern day applications and challenges by Aljuaid, Lamyaa Zaed, Koh, Tieng Wei, Sharif, Khaironi Yatim

    Published 2019
    “…Machine learning algorithms learned from available data. Further, this learning laid the foundation to develop AI for the various systems around us. …”
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  17. 17
    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA

    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

    Published 2012
    “…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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  18. 18
    Systematic review on missing data imputation techniques with machine learning algorithms for healthcare

    Systematic review on missing data imputation techniques with machine learning algorithms for healthcare by Ismail, Amelia Ritahani, Zainal Abidin, Nadzurah, Maen, Mohd Khaled

    Published 2022
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  19. 19
    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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  20. 20
    Octane number prediction for gasoline blends using convolution neural network / Zhu Yue

    Octane number prediction for gasoline blends using convolution neural network / Zhu Yue by Zhu , Yue

    Published 2021
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