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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
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  2. 2
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  3. 3
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  4. 4
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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  5. 5
    A web-based implementation of k-means algorithms

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

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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  6. 6
    A constructive task mapping algorithm for hard real-time embedded NoCs

    A constructive task mapping algorithm for hard real-time embedded NoCs by M. Norazizi Sham Mohd Sayuti, Indrusiak L.S.

    Published 2024
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  7. 7
    Design and statistical analysis of initial solution construction approach in curriculum based course timetabling problem

    Design and statistical analysis of initial solution construction approach in curriculum based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

    Published 2017
    “…This paper investigates the construction phase approach in which the sequential order of the courses/lectures applied several combination of graph heuristics to generate a population of initial solutions in curriculum-based course timetabling (CBCTT).The construction of population of initial solution is a prerequisite in a population-based metaheuristic implementation. …”
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  8. 8
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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  9. 9
    Constructing population of initial solutions for curriculum – based course timetabling problem

    Constructing population of initial solutions for curriculum – based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

    Published 2012
    “…Future work will use the best settings of heuristics to the improvement phase in population-based improvement algorithm.…”
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  10. 10
    Construction of initial solution population for curriculum-based course timetabling using combination of graph heuristics

    Construction of initial solution population for curriculum-based course timetabling using combination of graph heuristics by Wahid, Juliana, Mohd Hussin, Naimah

    Published 2016
    “…The construction of population of initial solution is a crucial task in population-based metaheuristic approach for solving curriculum-based university course timetabling problem because it can affect the convergence speed and also the quality of the final solution.This paper presents an exploration on combination of graph heuristics in construction approach in curriculum based course timetabling problem to produce a population of initial solutions.The graph heuristics were set as single and combination of two heuristics.In addition, several ways of assigning courses into room and timeslot are implemented.All settings of heuristics are then tested on the same curriculum based course timetabling problem instances and are compared with each other in terms of number of population produced.The result shows that combination of largest degree followed by saturation degree heuristic produce the highest number of population of initial solutions.The results from this study can be used in the improvement phase of algorithm that uses population of initial solutions…”
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  11. 11
    Sine-cosine optimization-based bijective substitution-boxes construction using enhanced dynamics of chaotic map

    Sine-cosine optimization-based bijective substitution-boxes construction using enhanced dynamics of chaotic map by Alzaidi, Amer Awad, Ahmad, Musheer, Ahmed, Hussam S., Al Solami, Eesa

    Published 2018
    “…This paper proposes a novel method of constructing strong substitution-boxes (S-boxes) of order n (4 ≤ n ≤ 8) based on a recent optimization algorithm known as sine-cosine algorithm (SCA). …”
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  12. 12
    Utilizing the roulette wheel based social network search algorithm for substitution box construction and optimization

    Utilizing the roulette wheel based social network search algorithm for substitution box construction and optimization by Kamal Z., Zamli, Alhadawi, Hussam S., Fakhrud Din, .

    Published 2023
    “…This paper introduces a new variant of a recent metaheuristic algorithm based on the Social Network Search algorithm (SNS), which is called the Roulette Wheel Social Network Search algorithm (SNS). …”
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  13. 13
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  14. 14
    Automated Examination Timetabling System (AETSys) / Ariff Md Ab Malik

    Automated Examination Timetabling System (AETSys) / Ariff Md Ab Malik by Md Ab Malik, Ariff, Haruddin, Hanitahaiza, Alwi, Anisah, Mohamed, Khainizam

    Published 2013
    “…This system has been developed based on a hybridization of local search-population based metaheuristic algorithms. …”
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  15. 15
    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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  16. 16
    An analysis of the parameter modifications in varieties of harmony search algorithm

    An analysis of the parameter modifications in varieties of harmony search algorithm by Nur Farraliza, Mansor, Zuraida, Abal Abas, Ahmad Fadzli Nizam, Abdul Rahman

    Published 2014
    “…A Harmony Search (HS) algorithm is a population based-meta-heuristics approach that is superior in solving diversified and large scale optimization problems. …”
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  17. 17
    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
    “…The IWD is a recent metaheuristic population-based algorithm belonging to the swarm intelligent category which simulates the dynamic of the river systems. …”
    thesis::doctoral thesis
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  18. 18
    An analysis of the parameter modifications in varieties of harmony search algorithm

    An analysis of the parameter modifications in varieties of harmony search algorithm by Mansor, N. F., Abal Abas, Zuraida, Abdul Rahman, Ahmad Fadzli Nizam, Shibghatullah, Abdul Samad, Safiah , Sidek

    Published 2014
    “…A Harmony Search (HS) algorithm is a population based-meta-heuristics approach that is superior in solving diversified and large scale optimization problems. …”
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  19. 19
    Sports tournament scheduling using genetic algorithm / Hafeezur Syakir Abdul Motok@Mohd Ridzuan

    Sports tournament scheduling using genetic algorithm / Hafeezur Syakir Abdul Motok@Mohd Ridzuan by Abdul Motok@Mohd Ridzuan, Hafeezur Syakir

    Published 2020
    “…In genetic algorithm, there are steps include such as initialize population, selection, crossover, mutation and calculate fitness. …”
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  20. 20
    Genetic algorithm techniques for the design of nonlinear microwave circuits

    Genetic algorithm techniques for the design of nonlinear microwave circuits by Arsat, Rashidah

    Published 2004
    “…By using Sample Balance's differential of current linear and nonlinear equation as an objective function, a Genetic Algorithm routine then been constructed. Genetic Algorithm will then recombine, mutate and evaluate the population of solution to find the best solution based on Sample balance equation. …”
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