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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
    Development of I-Complain@META: a complaint management system for FKMT students using naive bayes classification algorithm

    Development of I-Complain@META: a complaint management system for FKMT students using naive bayes classification algorithm by Cheah, Jia Ni

    Published 2024
    “…Development of I-Complain@META: a complaint management system for FKMT students using naive bayes classification algorithm by Cheah, Jia Ni…”
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  7. 7
    Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization

    Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization by Kamal Z., Zamli

    Published 2018
    “…Many meta-heuristic algorithms have been developed to date (e.g. …”
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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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    Citation Index Journal
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  9. 9
    Proposal of meta-requirement approach to analyze requirements specification completeness

    Proposal of meta-requirement approach to analyze requirements specification completeness by Muhamad Idaham, Umar Ong, M. A., Ameedeen

    Published 2018
    “…The objectives of this research are to identify the major factors in validating user requirements, development of a reverse engineered meta-requirement algorithm and validating with expert panel in requirements engineering of the algorithm usefulness. …”
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  10. 10
    Meta-requirement method towards analyzing completeness of requirements specification

    Meta-requirement method towards analyzing completeness of requirements specification by Muhamad Idaham, Umar Ong, Mohamed Ariff, Ameedeen, Imran Edzereiq, Kamarudin

    Published 2018
    “…However, due to time constraint, requirements validation steps are commonly ignored by developer. The objectives of this research are to identify the major factors in validating user requirements, development of a reverse engineered meta-requirement algorithm and validating with expert panel in requirements engineering of the algorithm usefulness. …”
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  11. 11
    An optimal LFC in two-area power systems using a meta-heuristic optimization algorithm

    An optimal LFC in two-area power systems using a meta-heuristic optimization algorithm by Najeeb M., Mansor M., Feyad H., Taha E., Abdullah G.

    Published 2023
    “…This meta-heuristic algorithm is called harmony search (HS), it is used to tune PI controller parameters (Kp, Kt) automatically. …”
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  12. 12
    Elitist hybrid migrating birds optimization and genetic algorithm based strategy for T-way test suite generation

    Elitist hybrid migrating birds optimization and genetic algorithm based strategy for T-way test suite generation by Hasneeza Liza, Zakaria

    Published 2020
    “…Although useful, much existing meta-heuristic based strategies have not sufficiently explored the adoption of more than one meta-heuristic to perform the search (termed hybridization). …”
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  13. 13
    Meta-heuristic structure for multiobjective optimization case study: Green sand mould system

    Meta-heuristic structure for multiobjective optimization case study: Green sand mould system by Ganesan, T., Elamvazuthi, I., KuShaari, K.Z., Vasant, P.

    Published 2014
    “…Analysis on the solution set produced by these algorithms is carried out using performance metrics. …”
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  14. 14
    Development of lung cancer prediction system using meta-heuristic optimized deep learning model

    Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

    Published 2023
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  15. 15
    A new meta heuristic evolutionary programming (NMEP) in optimizing economic energy dispatch

    A new meta heuristic evolutionary programming (NMEP) in optimizing economic energy dispatch by Mohamad Ridzuan, Mohamad Radzi, Hassan, Elia Erwani, Abdullah, Abdul Rahim, Bahaman, Nazrulazhar, Abdul Kadir, Aida Fazliana

    Published 2016
    “…The proposed optimization algorithm, namely New Meta-Heuristic Evolutionary Programming (NMEP) algorithm is followed to Meta-Heuristic Evolutionary Programming (Meta-EP) approach with some modification where the cloning process embedded as a significant progress during the implementation. …”
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  16. 16
    Symbiotic organisms search optimization algorithm in cloud computing: a nature-inspired meta-heuristic

    Symbiotic organisms search optimization algorithm in cloud computing: a nature-inspired meta-heuristic by Sa'ad, Suleiman, Abdullah, Muhammed, Abdullah, Azizol, Ayob, Fahrul Hakim

    Published 2022
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  17. 17
    Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions

    Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions by Mazlina, Abdul Majid, Alsariera, Yazan A., Alamri, Hammoudeh S., Nasser, Abdullah M., Kamal Z., Zamli

    Published 2014
    “…Over the last 30 years, many meta-heuristic algorithms have been developed in the literature including that of Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search Algorithm (HS) to name a few. …”
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  18. 18
    Embedded Meta evolutionary-firefly algorithm-ANN for multi dg planning in distribution system / Siti Rafidah Abdul Rahim

    Embedded Meta evolutionary-firefly algorithm-ANN for multi dg planning in distribution system / Siti Rafidah Abdul Rahim by Abdul Rahim, Siti Rafidah

    Published 2019
    “…In this study, Meta Evolutionary–Firefly Algorithm (EMEFA) was initially developed to expedite the computational time in multi-DG installation with improved accuracy. …”
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  19. 19
    An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming

    An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming by Mohamad Ridzuan, Mohamad Radzi

    Published 2018
    “…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
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  20. 20
    Comparative Analysis of Neighborhood based Meta-heuristic Algorithms for MC/DC Test Data Generation

    Comparative Analysis of Neighborhood based Meta-heuristic Algorithms for MC/DC Test Data Generation by Ariful, Haque, Kamal Z., Zamli

    Published 2016
    “…Most implementations have been focused on neighborhood-based meta-heuristics. In order to help test engineers to make informed decision on the best neighborhood based implementations, this paper investigates the size and time performance of two MC/DC test strategies re-implementation based on Simulated Annealing against two newly developed strategies based on Great Deluge and Late Acceptance Hill Climbing algorithms respectively. …”
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