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  1. 1
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…The project was planned using the Kanban development methodology, and was built using HTML, CSS, JavaScript, Django, NumPy and pandas. …”
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  2. 2
    Smart appointment organizer for mobile application / Mohd Syafiq Adam

    Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

    Published 2009
    “…The development of this project is based on a framework of 5 main stages: planning, analysis, design, implementation and testing. …”
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  3. 3
    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…This methodology consist of Requirement and Planning, Design, Construction, Testing and Implementation. …”
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  4. 4
    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer

    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer by Ahmad Nezer, Nurul Aqilah

    Published 2017
    “…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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  5. 5
    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment

    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment by Shaliza Hayati A. Wahab, Nordin Saad, Azali Saudi, Ali Chekima

    Published 2021
    “…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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  6. 6
    Implementation of RIO in UMJaNetSim / Chan Chin We

    Implementation of RIO in UMJaNetSim / Chan Chin We by Chan, Chin We

    Published 2004
    “…In this project, I will do some research on the recent TCP congestion control and avoidance mechanisms and implement one of the mechanisms into the Java Network Simulator (JaNetSim). …”
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  7. 7
    Songs Search Using Human Humming Voice

    Songs Search Using Human Humming Voice by Abdul Rahman, Mohamad Ariff

    Published 2007
    “…The scopes for this project are human humming voice, voice capture in WA V format, songs database, and MIDI file comparing algorithm. Methodologies used in this system are based on system analysis and design methodology comprising planning, analysis, design and implementation. …”
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  8. 8
    Particle swarm optimization for neural network learning enhancement

    Particle swarm optimization for neural network learning enhancement by Abdull Hamed, Haza Nuzly

    Published 2006
    “…In Backpropagation Neural Network (BPNN), there are many elements to be considered such as the number of input, hidden and output nodes, learning rate, momentum rate, bias, minimum error and activation/transfer functions. …”
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  9. 9
    The effect of adaptive parameters on the performance of back propagation

    The effect of adaptive parameters on the performance of back propagation by Abdul Hamid, Norhamreeza

    Published 2012
    “…The activation functions are adjusted by the adaptation of gain parameters together with adaptive momentum and learning rate value during the learning process. …”
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  10. 10
    Differential evolution for neural networks learning enhancement

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…In ANN, there are many elements need to be considered, and these include the number of input nodes, hidden nodes, output nodes, learning rate, momentum rate, bias parameter, minimum error and activation/transfer functions. …”
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  11. 11
    Green network planning and operational power consumption optimization in LTE-A using artificial intelligence

    Green network planning and operational power consumption optimization in LTE-A using artificial intelligence by Al-Samawi, Aida Ismail Ahmed

    Published 2015
    “…Moreover, the optimum rate of active relay is a function of the traffic pattern, average relay station load factor, their derivatives, and the relative RS to BS capacity factor. …”
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  12. 12
    Development of a scalable video compression algorithm

    Development of a scalable video compression algorithm by Khalifa, Othman Omran, Issa, Sinzobakwira, Olanweraju, Rashidah Funke, Al Khazmi, El Mahdi A

    Published 2012
    “…To improve the perceptual quality of coded video in a computation-constrained scenario, through controlling per-frame complexity, a rate-distortion optimised (RDO) rate control algorithm for encoding low bit rate video helped to achieve the target bitrates and PSNR using Lagrangian multiplier function. …”
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  13. 13
    Identification of vocal and voice disorders

    Identification of vocal and voice disorders by Murugesa Pandiyan, Paulraj, Prof. Madya Dr., Sazali, Yaacob, Prof. Dr., Mohd Rizon, Mohammed Juhari, Prof. Dr., Sivanandam, S. N., Muthusamy, Hariharan, Dr.

    Published 2011
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  14. 14
    Wireless network power optimization using relay stations blossoming and withering technique

    Wireless network power optimization using relay stations blossoming and withering technique by Al-Samawi, Aida, Sali, A., Nissirat, Liyth Ahmad, Noordin, Nor Kamariah, Othman, Mohamed, Hashim, Fazirulhisyam

    Published 2017
    “…In this paper, a new relay switching perspective is introduced for relay blossoming and withering algorithm. First, relay switching is considered as a function of time representing the rate of active relays. …”
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  15. 15
    Decentralized Adaptive Pi With Adaptive Interaction Algorithm Of Wastewater Treatment Plant

    Decentralized Adaptive Pi With Adaptive Interaction Algorithm Of Wastewater Treatment Plant by Rahmat, Mohd Fua'ad, Rahmat, Mohd Fuaad, Abdul Wahab, Norhaliza, Che Razali, Mashitah, Gaya, Muhammad Sani, Samsudin, Sharatul Izah

    Published 2014
    “…The error function is minimized directly by approximate Frechet tuning algorithm without explicit estimation of the model. …”
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  16. 16
    HF-AQM: An efficient active queue management scheme for wireless local area network environment

    HF-AQM: An efficient active queue management scheme for wireless local area network environment by Hassan, Suhaidi, Hassan, Atheer F., Arif, Suki

    Published 2017
    “…An Active Queue Management (AQM) is a proactive scheme that controls the network congestion by avoiding the congestion before it happened.When implementing AQM in wireless networks several contemporary issues must be considered, such as interference, collisions, multipath-fading, propagation distance, shadowing effects and route failure, and whether the wireless networks is WLAN or other type.Therefore, the needs for AQM algorithm that can perform in WLAN network as good and efficient as in wired network become so crucial.This paper proposes a new AQM algorithm called Hybrid Fair AQM (HF-AQM) that can achieve better fairness and higher utilization in WLAN environment by hybridizing queue delay and input rate to measure network congestion. …”
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  17. 17
    Smart student timetable planner

    Smart student timetable planner by Wong, Xin Tong

    Published 2025
    “…To achieve these objectives, the system adopts the Rapid Application Development (RAD) methodology, ensuring iterative design, prototyping, and user feedback integration throughout the process. The system is implemented using Node.js with Express for server-side development, HTML, CSS, and JavaScript for the frontend, and Socket.IO for real-time collaboration. …”
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  18. 18
    An efficient anomaly intrusion detection method with evolutionary neural network

    An efficient anomaly intrusion detection method with evolutionary neural network by Sarvari, Samira

    Published 2020
    “…Although activation functions are important for MLP to learn but for nonlinear complex functional mappings it has complicated calculation which reduces the accuracy of classification. …”
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  19. 19
    Smart fall detection by enhanced SVM with fuzzy logic membership function

    Smart fall detection by enhanced SVM with fuzzy logic membership function by Harum, Norharyati, Khalil, Mohamad Kchouri, Hazimeh, Hussein, Obeid, Ali

    Published 2023
    “…Because combining these two algorithms is not an easy task, we leverage SVM with a kernel comprised of a fuzzy membership function and thus build a new model known as FSVM. …”
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  20. 20
    Forecasting of photovoltaic output using hybrid particle swarm optimization-artificial neural network model / Muhamad Faizol Adli Abdullah

    Forecasting of photovoltaic output using hybrid particle swarm optimization-artificial neural network model / Muhamad Faizol Adli Abdullah by Abdullah, Muhamad Faizol Adli

    Published 2010
    “…In Backpropagation Neural Network (BPNN), there are many elements to be considered such as the number of input, hidden and output nodes, learning rate, momentum rate, bias, minimum error and activation/transfer functions. …”
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