Search Results - (( simulation competency based algorithm ) OR ( java application mining algorithm ))

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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
    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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  7. 7
    Competing risks for reliability analysis using Cox’s model

    Competing risks for reliability analysis using Cox’s model by Mohamed Elfaki, Faiz Ahmed, Daud, Isa, Ibrahim, Nor Azowa, Abdullah, M. Y., Usman, Mustofa

    Published 2007
    “…This paper seeks to show that, with a large sample size based on expectation maximization (EM) algorithm, both models give similar results. …”
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  8. 8
    Simulated Kalman Filter algorithms for solving optimization problems

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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  9. 9
    A novel clustering algorithm for mobile ad hoc networks based on determination of virtual links’ weight to increase network stability

    A novel clustering algorithm for mobile ad hoc networks based on determination of virtual links’ weight to increase network stability by Karimi, Abbas, Afsharfarnia, Abbas, Zarafshan, Faraneh, Syed Mohamed, Syed Abdul Rahman Al-Haddad

    Published 2014
    “…The performance of new algorithm is analyzed by using computer simulation. …”
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  10. 10
    Fuzzy adaptive emperor penguin optimizer for global optimization problems

    Fuzzy adaptive emperor penguin optimizer for global optimization problems by Md Abdul, Kader

    Published 2023
    “…The Emperor Penguin Optimizer (EPO) is a recently developed population-based metaheuristic algorithm that simulates the huddling behaviour of emperor penguins. …”
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  11. 11
    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation

    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

    Published 2022
    “…The proposed algorithm is simulated for simultaneous OPF-based conflicting objectives, respectively. …”
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  12. 12
    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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  13. 13
    Furniture form innovation and human–machine comfort evaluation model based on genetic algorithm

    Furniture form innovation and human–machine comfort evaluation model based on genetic algorithm by Yifan, Bai, Kamarudin, Khairul Manami, Alli, Hassan

    Published 2024
    “…This research explores the Pareto-primarily based Genetic Algorithm (PGA) inside this framework, with the goal of fostering innovation in product layout and the generation of novel ideas. …”
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  14. 14
    Cutpoint determination methods in competing risks subdistribution model

    Cutpoint determination methods in competing risks subdistribution model by Noor Akma Ibrahim, Abdul Kudus, Isa Daud, Mohd. Rizam Abu Bakar

    Published 2009
    “…Five cutpoint determination methods are developed based on regression of competing risks subdistribution. …”
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  15. 15
    Development of FRID based 2d localization simulation for autonomous guided vehicle tracking in indoor environment

    Development of FRID based 2d localization simulation for autonomous guided vehicle tracking in indoor environment by Al Hazza, Muataz Hazza Faizi, Zainal, Nur Izzati Zainal, Rodzi, Mohd Zuhaili Mohd

    Published 2018
    “…The mathematical process is coded in a software to produce a graphical user interface (GUI) based simulation for 2D localization of AGV tracking in indoor environment. …”
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  16. 16
    Cutpoint determination methods in competing risks subdistribution model

    Cutpoint determination methods in competing risks subdistribution model by Ibrahim, Noor Akma, Kudus, Abdul, Daud, Isa, Abu Bakar, Mohd Rizam

    Published 2009
    “…Five cutpoint determination methods are developed based on regression of competing risks subdistribution. …”
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  17. 17
    Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources

    Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

    Published 2021
    “…The detailed parametric analysis exhibits the competency of the proposed algorithm to explain the rheological features. …”
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  18. 18
    Multiple equations model selection algorithm with iterative estimation method

    Multiple equations model selection algorithm with iterative estimation method by Kamarudin, Nur Azulia, Ismail, Suzilah

    Published 2016
    “…This estimation method is equivalent to maximum likelihood estimation at convergence. Therefore, the algorithm is known as SUREIFGLS-Autometrics.Simulation and real data analyses were conducted to assess the performance of the algorithm.The simulation results reveal that the algorithm shows almost similar performances for all conditions involved. …”
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  19. 19
    Process Planning Optimization In Reconfigurable Manufacturing Systems

    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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  20. 20
    Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih

    Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih by Hashim, Asman

    Published 2001
    “…The system functions as a research instrument generating questionnaires as well as performing rubric assessment in information technology competency online. The data entered online using web as a medium and then executing back propagation simulation to obtain the desired neural network model, and to predict information technology competency based on the model obtained. …”
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