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  1. 1
    Solving university examination timetabling problem using intelligent water drops algorithm

    Solving university examination timetabling problem using intelligent water drops algorithm by Aldeeb B.A., Norwawi N.M., Al-Betar M.A., Jali M.Z.B.

    Published 2024
    Subjects: “…Intelligent water drops algorithm…”
    Conference Paper
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  2. 2
    Solving University Examination Timetabling Problem Using Intelligent Water Drops Algorithm

    Solving University Examination Timetabling Problem Using Intelligent Water Drops Algorithm by Aldeeb, BA, Norwawi, NM, Al-Betar, MA, Bin Jali, MZ

    Published 2024
    “…IWD is a recent metaheuristic population-based algorithm belonging to swarm intelligent category which simulate river system. …”
    Proceedings Paper
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  3. 3
    Intelligent Examination Timetabling System Using Hybrid Intelligent Water Drops Algorithm

    Intelligent Examination Timetabling System Using Hybrid Intelligent Water Drops Algorithm by AlDeeb, BA, Norwawi, NM, Al-Betar, MA, Jali, MZ

    Published 2024
    “…Intelligent Water Drops algorithm (IWD) is a population-based algorithm where each drop represents a solution and the sharing between the drops during the search lead to better drops. …”
    Proceedings Paper
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  4. 4
    Intelligent examination timetabling system using hybrid intelligent water drops algorithm

    Intelligent examination timetabling system using hybrid intelligent water drops algorithm by AlDeeb, Bashar A., Md Norwawi, Norita, Al-Betar, Mohammed A., Jali, Mohd Z.

    Published 2015
    “…This paper proposes Hybrid Intelligent Water Drops (HIWD) algorithm to solve Tamhidi programs uncapacitated examination timetabling problem in Universiti Sains Islamic Malaysia (USIM).Intelligent Water Drops algorithm (IWD) is a population-based algorithm where each drop represents a solution and the sharing between the drops during the search lead to better drops.The results of this study prove that the proposed algorithm can produce a high quality examination timetable in shorter time in comparison with the manual timetable.…”
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  5. 5
    Modified And Ensemble Intelligent Water Drop Algorithms And Their Applications

    Modified And Ensemble Intelligent Water Drop Algorithms And Their Applications by O. F. Alijla, Basem

    Published 2015
    “…Pertama, algoritma TAC yang diubahsuai, diperkenalkan. The Intelligent Water Drop (IWD) algorithm is a swarm-based model that is useful for undertaking optimization problems. …”
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    Thesis
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  6. 6
    Hybrid Intelligent Water Drops Algorithm For Examination Timetabling Problem

    Hybrid Intelligent Water Drops Algorithm For Examination Timetabling Problem by Bashar A.Aldeeb, Mohammed Azmi Al-Betar, Norita Md Norwawi, Khalid A.Alissa, Mutasem K.Alsmadi, Ayman A.Hazaymeh, Malek Alzaqebah

    Published 2024
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  7. 7
    Optimization and prediction of battery electric vehicle driving range using adaptive fuzzy technique

    Optimization and prediction of battery electric vehicle driving range using adaptive fuzzy technique by Abulifa, Abdulhadi Abdulsalam

    Published 2022
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  8. 8
    Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems

    Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems by Bashar AbedAl Mohdi Talal AlDeeb

    Published 2024
    “…This thesis presents an investigation of using the Intelligent Water Drops (IWD) algorithm to construct and produce good quality solutions for the UETP. …”
    thesis::doctoral thesis
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  9. 9
    Hybrid model to improve the river streamflow forecasting utilizing multi-layer perceptron-based intelligent water drop optimization algorithm

    Hybrid model to improve the river streamflow forecasting utilizing multi-layer perceptron-based intelligent water drop optimization algorithm by Pham Q.B., Afan H.A., Mohammadi B., Ahmed A.N., Linh N.T.T., Vo N.D., Moazenzadeh R., Yu P.-S., El-Shafie A.

    Published 2023
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  10. 10
    Energy Management Strategies for Optimal Hybrid Microgrid Configuration in the Smart Village Context

    Energy Management Strategies for Optimal Hybrid Microgrid Configuration in the Smart Village Context by Fakhar, Adila

    Published 2018
    “…A part of the developed algorithm is used to deal with the optimal scheduling control while the other actuates the dynamic demand response based PV power forecasting. …”
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  11. 11
    Design and Implementation of Intelligent Interoperability Framework for Heterogeneous Subsystems in Smart Home Environment

    Design and Implementation of Intelligent Interoperability Framework for Heterogeneous Subsystems in Smart Home Environment by Perumal, Thinagaran

    Published 2011
    “…The third algorithm, named as Pro-Active Intelligence algorithm has inspired autonomous action triggering for each event interoperation, using a control action statement that is generated by SOAP packets required for joint execution of tasks among heterogeneous subsystems. …”
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  12. 12
    Design and Development of Artificial Intelligence (Al)-Based Desicion Support System For Manufacturing Applications

    Design and Development of Artificial Intelligence (Al)-Based Desicion Support System For Manufacturing Applications by Lim , Chee Peng

    Published 2016
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    Monograph
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  13. 13
    Mining sequence of event from vector-based spatiotemporal database

    Mining sequence of event from vector-based spatiotemporal database by B.Y., Widodo

    Published 2007
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  14. 14
    A comparative study and simulation of object tracking algorithms

    A comparative study and simulation of object tracking algorithms by Ji, Yuanfa, Yin, Pan, Sun, Xiyan, Kamarul Hawari, Ghazali, Guo, Ning

    Published 2020
    “…This article introduces the popular object tracking algorithms, from common problems in object tracking to the classification of algorithms: Early classic trackingalgorithms, tracking algorithms based on kernel correlation filtering, and tracking algorithms based on deep learning. …”
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  15. 15
    A lightweight graph-based pattern recognition scheme in mobile ad hoc networks.

    A lightweight graph-based pattern recognition scheme in mobile ad hoc networks. by Raja Mahmood, Raja Azlina, Muhamad Amin, Anang Hudaya, Amir, Amiza, Khan, Asad I.

    Published 2012
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  16. 16
    A real-time integrated fire detection and alarm (FDA) system for network based building automation

    A real-time integrated fire detection and alarm (FDA) system for network based building automation by Anwar, Farhat, Islam, Rounakul, Hussain, Sabahat, Rashid, Muhammad Mahbubur, Shaikh, Zuhaib

    Published 2017
    “…Objectives: An integrated Fire Detection and Alarm (FDA) systems with building automation was studied, to reduce cost and improve their reliability by preventing false alarm, signal drop and network breakdown. This work proposes an improved framework for FDA system to ensure a robust, intelligent network of FDA control panels in real-time. …”
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  17. 17
    CSC583 - Artificial Intelligence Algorithms / College of Computing, Informatics and Media

    CSC583 - Artificial Intelligence Algorithms / College of Computing, Informatics and Media by UiTM, College of Computing, Informatics and Media

    Published 2018
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  18. 18
    CSC583: Artificial Intelligence Algorithms / College of Computing, Informatics and Mathematics

    CSC583: Artificial Intelligence Algorithms / College of Computing, Informatics and Mathematics by UiTM, College of Computing, Informatics and Mathematics

    Published 2018
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  19. 19
    Modelling and optimisation of blood glucose control for type 1 diabetes using multi-parametric programming and model-based predictive control (mp-MPC) / Associate Professor Dr Ayub Md. Som

    Modelling and optimisation of blood glucose control for type 1 diabetes using multi-parametric programming and model-based predictive control (mp-MPC) / Associate Professor Dr Ayub... by Md. Som, Ayub

    Published 2014
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  20. 20
    IOT Based Smart Wastewater Treatment Model for Industry 4.0 Using Artificial Intelligence

    IOT Based Smart Wastewater Treatment Model for Industry 4.0 Using Artificial Intelligence by Singh, D.N., Murugamani, C., Kshirsagar, P.R., Tirth, V., Islam, S., Qaiyum, S., Suneela, B., Al Duhayyim, M., Waji, Y.A.

    Published 2022
    “…Goal of this approach is to treat the wastewater treatment model with industrial data. Algorithms of the artificial neural network (ANN) were employed progressively to predict parameters for wastewater plants. …”
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