Search Results - (( java implementation mining algorithm ) OR ( problem model method algorithm ))

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  1. 1

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

    Published 2012
    “…The proposed method, XiFLEX has been implemented using two different techniques (java based & XQuery) and compared with the original FLEX algorithm in its basic implementation and the Apriori algorithm for frequent patterns generation. …”
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    Thesis
  2. 2

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

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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    Thesis
  3. 3

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

    Published 2019
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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    Article
  4. 4

    Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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    Conference or Workshop Item
  5. 5

    Mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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    Conference or Workshop Item
  6. 6

    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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    Final Year Project / Dissertation / Thesis
  7. 7

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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    Thesis
  8. 8

    Development of committee machine models for multiple response optimization problems by Golestaneh, Seyed Jafar

    Published 2014
    “…Four methodologies are to make four different CM models to solve MRO problems. The fifth methodology proposes the final algorithm which uses four CM models together to solve MRO problems. …”
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    Thesis
  9. 9

    Comparison Between the Bees Algorithm and Genetic Algorithm Model in Manpower Allocation on Cell Loading Problem by AlMahasneh, Hossam Sayel

    Published 2010
    “…This research not only analyzes the MACL problem with a mathematical model and genetic algorithm (GA) and the Bees Algorithm but also it make a comparison among the mathematical models to measure the efficiency of the stated algorithm in solving the number of tardy jobs concept and also adds original aspects, the Cell Formation, the traditional GA methods. …”
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    Thesis
  10. 10

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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    Undergraduates Project Papers
  11. 11

    Comparison of Some Numerical Methods for Solving Real-Life Nonlinear Equations by Using Python Programming / Annie Gorgey ... [et al.] by Gorgey, Annie, Zulkifly, Zul Hafiezy, Hassim, Haslinah, Azim, Farah Adilla

    Published 2024
    “…The results indicate that the Secant method requires fewer iterations and CPU time if compared with Newton-Raphson, Bisection and Algorithm 1 in solving fluid permeability problems, blood rheology models, and Van Der Wall’s problems. …”
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    Article
  12. 12
  13. 13

    Modelling and Optimization of Asymmetric Vehicle Routing Problem Using Particle Swarm Optimization Algorithm by Muhamad Rozikin, Kamaluddin, M. F. F., Ab Rashid

    Published 2021
    “…Specific optimization model and algorithm were developed to solve the problem. …”
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    Conference or Workshop Item
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    Solving the integrated inventory supply chain problems using meta-heuristic methods / Seyed Mohsen Mousavi by Seyed Mohsen , Mousavi

    Published 2018
    “…As the mixed integer nonlinear model of the problem was complicated to solve using exact methods, several meta-heuristic algorithms were employed in to optimize the models under investigation. …”
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    Thesis
  17. 17

    Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling by Shimailawi, Shatha Abdulhadi Muthana

    Published 2022
    “…Present graph models cannot generate schedule for the multi-objective GMS models while existing Pareto Ant Colony System (PACS) algorithms were not able to consider the two problems separately. …”
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    Thesis
  18. 18

    Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

    Published 2019
    “…Another problem is estimating the covariance matrix of the parameter estimators, since the existing methods involve derivative of the hazard function of the model’s error terms. …”
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    Thesis
  19. 19

    New Quasi-Newton Equation And Method Via Higher Order Tensor Models by Gholilou, Fahimeh Biglari

    Published 2010
    “…The new method yields a more efficient algorithm compared to the standard limited memory BFGS with simple bounds (L-BFGS-B) method in the case of solving unconstrained problems. …”
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    Thesis
  20. 20

    Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    Published 2012
    “…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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    Conference or Workshop Item