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  1. 1
    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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  2. 2
    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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  3. 3
    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…”
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  4. 4
    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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  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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  6. 6
    Modeling of static and dynamic components of bio-nanorobotic systems

    Modeling of static and dynamic components of bio-nanorobotic systems by Gavgani, Hamidreza Khataee

    Published 2012
    “…The first modeling technique applies graph algorithms to compute a new set of optimal weighted structural properties of C60 and C70 fullerenes. …”
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  7. 7
    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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  8. 8
    The application of suitable sports games for junior high school students based on deep learning and artificial intelligence

    The application of suitable sports games for junior high school students based on deep learning and artificial intelligence by Ji, Xueyan, Samsudin, Shamsulariffin, Hassan, Muhammad Zarif, Farizan, Noor Hamzani, Yuan, Yubin, Chen, Wang

    Published 2025
    “…Then it constructs a spatio-temporal graph model, which represents human skeleton points as nodes in the graph and the connectivity between nodes as edges. …”
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  9. 9
    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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  10. 10
    African Buffalo Optimization (ABO): A New Metaheuristic Algorithm

    African Buffalo Optimization (ABO): A New Metaheuristic Algorithm by Odili, Julius Beneoluchi, M. N. M., Kahar

    Published 2015
    “…The African Buffalo Optimization (A.B.0) algorithm simulates the African buffalos' behaviour by encapsulation in a mathematical model; which solves a number of discrete optimization problems using graph-based route planning, job scheduling and it extends Swarm Intelligence paradigms. …”
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  11. 11
    Heuristic factors in ant system algorithm for course timetabling problem

    Heuristic factors in ant system algorithm for course timetabling problem by Djamarus, Djasli, Ku-Mahamud, Ku Ruhana

    Published 2009
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  12. 12
    VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS.

    VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS. by FAROOQ, HUMERA

    Published 2012
    “…The Genetic Algorithm is an area in the field of Artificial Intelligence that is founded on the principles of biological evolution. …”
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  13. 13
    Enhanced Community Detection Based On Cross Time For Higher Visibility In Supply Chain: A Six-Steps Model Framework

    Enhanced Community Detection Based On Cross Time For Higher Visibility In Supply Chain: A Six-Steps Model Framework by Abal Abas, Zuraida, Mohd Zaki, Nurul Hafizah, Asmai, Siti Azirah, Abdul Rahman, Ahmad Fadzli Nizam, Zainal Abidin, Zaheera

    Published 2019
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  14. 14
    Optimization of Maximum Power Point Tracking (MPPT) of Photovoltaic System using Artificial Intelligence (AI) Algorithms

    Optimization of Maximum Power Point Tracking (MPPT) of Photovoltaic System using Artificial Intelligence (AI) Algorithms by Raal Mandour, Raal

    Published 2013
    “…Artificial intelligence algorithms, specifically PSO and PSO combined with Incremental conductance algorithm, are used to achieve the stated goals. …”
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  15. 15
    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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  16. 16
    Solving a backtracking intelligently : a case study / Muthukkaruppan Annamalai

    Solving a backtracking intelligently : a case study / Muthukkaruppan Annamalai by Annamalai, Muthukkaruppan

    Published 2001
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  17. 17
    Leveraging artificial intelligence in modern supply chains

    Leveraging artificial intelligence in modern supply chains by Ng, Qiao Ying

    Published 2025
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  18. 18
    Agarwood oil grade clustering of aquilaria malaccensis species using Extraction by GC-MS analysis: Efficient KNN algorithm based on patterns visualization of two-dimensional graph

    Agarwood oil grade clustering of aquilaria malaccensis species using Extraction by GC-MS analysis: Efficient KNN algorithm based on patterns visualization of two-dimensional graph by Siti Mariatul Hazwa, Mohd Huzir, Anis Hazirah ‘Izzati H., Al-Hadi, Amir Hussairi, Zaidi, Nurlaila F., Ismail, Zakiah, Mohd Yusoff, Saiful Nizam, Tajuddin, Mohd Nasir, Taib

    Published 2024
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  19. 19
    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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  20. 20
    Nonlinear convergence algorithm: structural properties with doubly stochastic quadratic operators for multi-agent systems

    Nonlinear convergence algorithm: structural properties with doubly stochastic quadratic operators for multi-agent systems by Abdulghafor, Rawad Abdulkhaleq Abdulmolla, Turaev, Sherzod, Zeki, Akram M., Adamu, Abubakar Ibrahim

    Published 2018
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