Search Results - (( developing set partitioning algorithm ) OR ( java implication based algorithm ))

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  1. 1

    An enhanced soft set data reduction using decision partition order technique by Mohammed, Mohammed Adam Taheir

    Published 2017
    “…Also, the accuracy of original soft-set optimal and sub-optimal results have been improved using an intelligent SSR-BPSO-BBO algorithm. …”
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    Thesis
  2. 2

    Implementation Of Hardware Software Partitioning In Embedded System by Mohd Nor, Masyirah

    Published 2018
    “…PSO and GA algorithm are chosen in this project to perform hardware software partitioning using Python 2.7.14. …”
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    Monograph
  3. 3

    Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

    Published 2019
    “…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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    Thesis
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    Soft Set Decision/Forecasting System Based on Hybrid Parameter Reduction Algorithm by Mohammed, Mohammed Adam Taheir, Sadiq, Ali Safa, Ruzaini, Abdullah Arshah, Ernawan, Ferda, Mirjalili, Seyedali

    Published 2017
    “…The contributions of this study are mainly focused on minimizing choices costs through adjusting the original classifications by decision partition order and enhancing the probability of search domain by a developed HPC algorithm. …”
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    Article
  6. 6

    Parallel Optical Window Algorithm Applied to Optical Multistage Interconnection Network by Othman, Mohamed, Abdullah, Monir, Johari, Rozita

    Published 2008
    “…In this paper, a new parallel algorithm of the window method is developed called the Balanced Parallel Window Method (BPWM) algorithm. …”
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    Article
  7. 7

    New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

    Published 2000
    “…The split-condition-merge-reduct algorithm ( SCMR) was performed on three different modules: partitioning the data set vertically into subsets, applying rough set concepts of reduction to each subset, and merging the reducts of all subsets to form the best reduct. …”
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    Thesis
  8. 8

    Ensemble Framework for Motif Discovery Based on Data Partitioning by Choong, Allen Chieng Hoon

    Published 2020
    “…Another set of datasets are gathered and sampled without partitioning. …”
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    Thesis
  9. 9

    Data clustering using the bees algorithm by Pham, D.T, Otri, S., Afify, A., Mahmuddin, Massudi, Al-Jabbouli, H.

    Published 2007
    “…The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. …”
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    Conference or Workshop Item
  10. 10

    DNA Motif Prediction using Novel Ensemble Approach by Choong, Allen Chieng Hoon

    Published 2020
    “…Another set of datasets are gathered and sampled without partitioning. …”
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    Thesis
  11. 11

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

    Published 2009
    “…Thus, we consider the problem of obtaining a threshold value of a continuous covariate given a competing risk survival time response using a binary partitioning algorithm as a way to optimally partition data into two disjoint sets. …”
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    Article
  12. 12
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    The new efficient and accurate attribute-oriented clustering algorithms for categorical data by Qin, Hongwu

    Published 2012
    “…IG-ANMI algorithm improves G-ANMI by developing a new attribute-oriented initialization method in which part of initial chromosomes is generated by using the attributes partitions. …”
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    Thesis
  14. 14

    Dynamic area coverage algorithms for static and mobile wireless sensor network environments using voronoi techniques by Ceesay, Omar M.

    Published 2011
    “…Voronoi tessellation consists of a set of sites in a plane partitioned in such a way that the entire region within any one of the partitions is closest to only one site than to any other site in the plane. …”
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    Thesis
  15. 15

    Ant system and weighted voting method for multiple classifier systems by Husin, Abdullah, Ku-Mahamud, Ku Ruhana

    Published 2018
    “…A diverse classifier ensemble is constructed by training them with different feature set partitions. The ant system-based algorithm is used to form the optimal feature set partitions. …”
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    Article
  16. 16

    Automated time series forecasting by Ismail, Suzilah, Zakaria, Rohaiza, Tuan Muda, Tuan Zalizam

    Published 2011
    “…Moving Average, Decomposition, Exponential Smoothing, Time Series Regressions and ARIMA) were used.The algorithm was developed in JAVA using up to date forecasting process such as data partition, several error measures and rolling process.Successfully, the results of the algorithm tally with the results of SPSS and Excel.This automatic forecasting will not just benefit forecaster but also end users who do not have in depth knowledge about forecasting techniques.…”
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    Monograph
  17. 17

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

    Published 2009
    “…Thus, we consider the problem of obtaining a threshold value of a continuous covariate given a competing risk survival time response using a binary partitioning algorithm as a way to optimally partition data into two disjoint sets. …”
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    Article
  18. 18

    Improved clustering using robust and classical principal component by Hassn, Ahmed Kadom

    Published 2017
    “…k-means algorithm is a popular data clustering algorithm. k-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. …”
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    Thesis
  19. 19

    Tree-based contrast subspace mining method by Florence Sia Fui Sze

    Published 2020
    “…The research works involve first preparing the real world numerical and categorical data sets. Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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    Thesis
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