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  1. 1
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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  2. 2
    SecPath: Energy efficient path reconstruction in wireless sensor network using iterative smoothing

    SecPath: Energy efficient path reconstruction in wireless sensor network using iterative smoothing by Abd, Wamidh Jwdat

    Published 2019
    “…This work uses iterative smoothing algorithm to find an alternative path with less distance and energy consumption. …”
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  3. 3
    Energy efficient path reconstruction in wireless sensor network using iPath

    Energy efficient path reconstruction in wireless sensor network using iPath by Hasan, Sazlinah, Abd, Wamidh Jwdat, Ariffin, Ahmad Alauddin

    Published 2019
    “…This work uses iterative boosting algorithm to find an alternative path with less distance and energy consumption. …”
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  4. 4
    Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem

    Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem by Ismail, Ibrahim, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2015
    “…In this study, rule-based multi-state gravitational search algorithm (RBMSGSA) algorithm is proposed to solve discrete combinatorial optimization problems. …”
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  5. 5
    Visdom: Smart guide robot for visually impaired people

    Visdom: Smart guide robot for visually impaired people by Lee, Zhen Ting

    Published 2025
    “…Core functionalities such as path planning, autonomous movement, voice feedback, and app-to-robot communication have been thoroughly tested and optimized. …”
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    Final Year Project / Dissertation / Thesis
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  6. 6
    Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems

    Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems by Bibi Amirah Shafaa, Emambocus

    Published 2024
    “…The steepest-ascent hill climbing algorithm is used as a local search technique to improve the exploitation of the adapted discrete DA. …”
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  7. 7
    Design of dictionary based on Discrete Tchebichef Transform

    Design of dictionary based on Discrete Tchebichef Transform by Qayyum A., Malik A.S., Nuafal M., Iqbal M., Abdullah T.A.R.B.T.

    Published 2023
    Conference Paper
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  8. 8
    Multi-state PSO GSA for solving discrete combinatorial optimization problems

    Multi-state PSO GSA for solving discrete combinatorial optimization problems by Ismail, Ibrahim

    Published 2016
    “…These four algorithms can be used to solve discrete combinatorial optimization problems (COPs). …”
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  9. 9
    Formulating new enhanced pattern classification algorithms based on ACO-SVM

    Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
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  10. 10
    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems

    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

    Published 2011
    “…This thesis describes the development of an efficient algorithm for solving nonlinear stochastic optimal control problems in discrete-time based on the principle of model-reality differences. …”
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  11. 11
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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  12. 12
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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  13. 13
    Model structure selection for a discrete-time non-linear system using genetic algorithm

    Model structure selection for a discrete-time non-linear system using genetic algorithm by Ahmad, Robiah, Jamaluddin , Hishamuddin, Hussain, Mohd. Azlan

    Published 2004
    “…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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  14. 14
    Denosing of natural image based on non-linear threshold filtering using discrete wavelet transformation

    Denosing of natural image based on non-linear threshold filtering using discrete wavelet transformation by Khmag, Asem, Ramli, Abdul Rahman, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Hashim, Shaiful Jahari

    Published 2014
    “…This paper treats with threshold estimation technique to reduce the noise in natural images by using on discrete wavelet transformation. Calculating the value of thresholding, the way it works in the algorithm (derivation of thresholding function) and the type of wavelet mother functions, are pivotal issues in the field of denoising based wavelet approach. …”
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  15. 15
    Chebyshev approximation of discrete polynomials and splines

    Chebyshev approximation of discrete polynomials and splines by Che Seman, Fauziahanim

    Published 2004
    “…This work is concerned with the approximation of discrete data using polynomials and splines based on the Chebyshev approximation criterion. …”
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  16. 16
    Chebyshev approximation of discrete polynomials and splines

    Chebyshev approximation of discrete polynomials and splines by Che Seman, Fauziahanim

    Published 2004
    “…This work is concerned with the approximation of discrete data using polynomials and splines based on the Chebyshev approximation criterion. …”
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  17. 17
    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling

    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

    Published 2022
    “…It is also discovered that the hybrid-discrete MOPSO (HD-MOPSO) algorithm manages to obtain higher values in the performance metrics consisting of non-dominance ratio and hypervolume compared to the competing algorithms. …”
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  18. 18
    Assisted History Matching by Using Genetic Algorithm and Discrete Cosine Transform

    Assisted History Matching by Using Genetic Algorithm and Discrete Cosine Transform by Abdul Rashid, Abdul Hadi

    Published 2014
    “…Later, an algorithm combining both Genetic Algorithm and Discrete Cosine Transform was proposed, which shows the step-by-step sequence of both methods. …”
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    Final Year Project
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  19. 19
    A Modified Gravitational Search Algorithm for Discrete Optimization Problem

    A Modified Gravitational Search Algorithm for Discrete Optimization Problem by Zuwairie, Ibrahim, Zulkifli, Md. Yusof, Shahdan, Sudin, Sophan Wahyudi, Nawawi, Amar Faiz, Zainal Abidin, Muhammad Arif, Abdul Rahim, Kamal, Khalil

    Published 2014
    “…This paper presents a modified Gravitational Search Algorithm (GSA) called Discrete Gravitational Search Algorithm (DGSA) for discrete optimization problems. …”
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  20. 20
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, Mohd Azlan

    Published 2004
    “…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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