Search Results - (( parameter adaptation process algorithm ) OR ( java implementation case algorithm ))

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  1. 1
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
    “…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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  2. 2
    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh

    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

    Published 2015
    “…The second taxonomy is a new taxonomy proposed to classify the adaptive DE algorithms in particular into two categories (DE with adaptive parameters and DE with adaptive parameters and strategies) considering the adaptive components used in this algorithm. …”
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  3. 3
    Exploring dynamic self-adaptive populations in differential evolution

    Exploring dynamic self-adaptive populations in differential evolution by Teo, Jason Tze Wi

    Published 2006
    “…In this paper, we present a first attempt at self-adapting the population size parameter in addition to self-adapting crossover and mutation rates. …”
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  4. 4
    Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework

    Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework by Asaad Aref, Ibrahim

    Published 2004
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  5. 5
    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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  6. 6
    DESIGN OF ADAPTIVE BACKSTEPPING WITH GRAVITATIONAL SEARCH ALGORITHM FOR NONLINEAR SYSTEM

    DESIGN OF ADAPTIVE BACKSTEPPING WITH GRAVITATIONAL SEARCH ALGORITHM FOR NONLINEAR SYSTEM by Md Rozali, Sahazati, RAHMAT, MOHD FUA'AD, HUSAIN, ABDUL RASHID, Kamarudin, Muhammad Nizam

    Published 2014
    “…Gravitational search algorithm (GSA) is integrated with the designed controller in order to automatically tune its control parameters and adaptation gain since the tracking performance of the controller relies on these parameters. …”
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  7. 7
    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 Pi controller parameters are obtained by using simple updating algorithm developed based on adaptive interaction theory. …”
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  8. 8
    Pairwise testing tools based on hill climbing algorithm (PTCA)

    Pairwise testing tools based on hill climbing algorithm (PTCA) by Lim, Seng Kee

    Published 2014
    “…The actual implementation of the algorithm which is in Java programming language, the program is implemented on Net Bean 7.0.1. …”
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    Undergraduates Project Papers
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  9. 9
    A hybrid adaptive harmony search with modified great deluge algorithm for school timetabling

    A hybrid adaptive harmony search with modified great deluge algorithm for school timetabling by Arbaoui, Billel

    Published 2025
    “…Phase 2 adaptively tunes parameters based on iteration position, solution number, behavioral status, and parameter linkages. …”
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  10. 10
    Examination timetabling using genetic algorithm case study: KUiTTHO

    Examination timetabling using genetic algorithm case study: KUiTTHO by Mohd Salikon, Mohd Zaki

    Published 2005
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  11. 11
    Self-adaptive Population Size Strategy Based on Flower Pollination Algorithm for T-Way Test Suite Generation

    Self-adaptive Population Size Strategy Based on Flower Pollination Algorithm for T-Way Test Suite Generation by Abdullah, Nasser, Kamal Z., Zamli

    Published 2019
    “…In the proposed algorithm, the population size of FPA is dynamically varied based on the current need of the search process. …”
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  12. 12
    Java based expert system for selection of natural fibre composite materials

    Java based expert system for selection of natural fibre composite materials by Ahmed Ali, Basheer A., Salit, Mohd Sapuan, Zainudin, Edi Syams, Othman, Mohamed

    Published 2013
    “…In this paper, we develop a technology for the materials selection system using Java based expert system. The weighted-range method (WRM) was implemented to identify the range value and to scrutinise the candidate materials. …”
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  13. 13
    Adaptive-model based self-tuning generalized predictive control of a biodiesel reactor / Ho Yong Kuen

    Adaptive-model based self-tuning generalized predictive control of a biodiesel reactor / Ho Yong Kuen by Ho, Yong Kuen

    Published 2011
    “…Several RLS algorithms were screened and the Variable Forgetting Factor Recursive Least Squares (VFF-RLS) algorithm was selected to capture the dynamics of the process online for the purpose of model adaptation in the controller. …”
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  14. 14
    Parameter adaptation for ant colony system in wireless sensor network

    Parameter adaptation for ant colony system in wireless sensor network by Abdul Nasir, Husna Jamal, Ku-Mahamud, Ku Ruhana, Kamioka, Eiji

    Published 2019
    “…Most researches are focused on optimizing the routing process by using predefined parameters within a certain range. …”
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  15. 15
    Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO

    Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO by Mohd. Zaki, Mohd. Salikon

    Published 2005
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  16. 16
    A self-adaptive agent-based simulation modelling framework for dynamic processes

    A self-adaptive agent-based simulation modelling framework for dynamic processes by Ling, Loo Yim, Dr.

    Published 2023
    “…Key parameters for dynamic processes of different domains were formulated for the construction of self-adaptive simulation algorithms and modelling. …”
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  17. 17
    A comparative study for parameter selection in online auctions

    A comparative study for parameter selection in online auctions by Gan, Kim Soon

    Published 2009
    “…The bidding strategies applying self-adaptation model are expected to perform better than the deterministic dynamic adaptation because of the nature of the algorithm itself. …”
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  18. 18
    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT

    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

    Published 2023
    “…According to the simulation results, the proposed algorithm produces the best solution among all algorithms in the proposed cases. � 2021 Little Lion Scientific…”
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  19. 19
    A Self-Adaptive Agent-Based Dynamic Processes Simulation Modelling Framework

    A Self-Adaptive Agent-Based Dynamic Processes Simulation Modelling Framework by Loo Y.L., Ahmad A., Mustapha A., Mostafa S.A.

    Published 2023
    Conference Paper
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  20. 20
    Nature-inspired parameter controllers for ACO-based reactive search

    Nature-inspired parameter controllers for ACO-based reactive search by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

    Published 2015
    “…This study proposes machine learning strategies to control the parameter adaptation in ant colony optimization algorithm, the prominent swarm intelligence metaheuristic.The sensitivity to parameters’ selection is one of the main limitations within the swarm intelligence algorithms when solving combinatorial problems.These parameters are often tuned manually by algorithm experts to a set that seems to work well for the problem under study, a standard set from the literature or using off-line parameter tuning procedures. …”
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