Search Results - (( using selection _ algorithm ) OR ( java application stemming algorithm ))

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  1. 1

    Static and self-scalable filter range selection algorithms for peer-to-peer networks by Kweh, Yeah Lun

    Published 2011
    “…Two multiple selection algorithm, which are known as “static filter range selection algorithm” and “self-scalable selection algorithm” are proposed. …”
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    Thesis
  2. 2

    Optimization of attribute selection model using bio-inspired algorithms by Basir, Mohammad Aizat, Yusof, Yuhanis, Hussin, Mohamed Saifullah

    Published 2019
    “…Attribute selection which is also known as feature selection is an essential process that is relevant to predictive analysis.To date, various feature selection algorithms have been introduced, nevertheless they all work independently. …”
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    Article
  3. 3

    Routing performance enhancement in hierarchical torus network by link-selection algorithm by Rahman, M.M. Hafizur, Horiguchi, Susumu

    Published 2005
    “…We find that the dynamic communication performance of an HTN using the link-selection algorithm is better than when the dimension-order routing algorithm is used.…”
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    Article
  4. 4

    Evaluation of feature selection algorithm for android malware detection by Mazlan, Nurul Hidayah, A Hamid, Isredza Rahmi

    Published 2018
    “…The related best features in the sample are selected using weight and priority ranking process. …”
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    Article
  5. 5

    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

    Published 2022
    “…The second modification develops a new position update mechanism using the Bat Algorithm movement. The third modification improves the controlled parameter of the MBGWO algorithm using indicators from the search process to refine the solution. …”
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    Thesis
  6. 6

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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    Thesis
  7. 7

    AGENT MEETING SCHEDULER by ZAINAL ABIDIN, NURAINI

    Published 2011
    “…An agent meeting scheduler prototype then will be developed to prove that the selected algorithm is working properly. Qualitative research method is being used to gather necessary data on agent algorithm and this data will be used to select the suitable algorithm. …”
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    Final Year Project
  8. 8

    Intership supervisor selection using genetic algorithms by Karim, Junaida

    Published 2015
    “…By using genetic algorithm approach, the priority factors for the assigning faculty supervisor to internship student has been identified and also development model of selection has been done to fulfill the criteria for the selection specified by the FTMK. …”
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    Thesis
  9. 9

    Daily rainfall prediction using clonal selection algorithm by Noor Rodi, Nur Syazwani, Ismail , Amelia Ritahani, Abdul Malik, Marlinda

    Published 2012
    “…The common use of Clonal Selection Algorithm is to randomly generate the antibodies in the population. …”
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    Proceeding Paper
  10. 10

    Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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    Article
  11. 11

    Model structure selection for a discrete-time non-linear system using genetic algorithm by Ahmad, Robiah, Jamaluddin , Hishamuddin, Hussain, Mohd. Azlan

    Published 2004
    “…The results show that the proposed algorithm can be employed as an algorithm to select the structure of the proposed model.…”
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    Article
  12. 12

    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

    Published 2020
    “…An improved version of Salp Swarm Algorithm (ISSA) is proposed in this study to solve feature selection problems and select the optimal subset of features in wrapper-mode. …”
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    Article
  13. 13

    Improved whale optimization algorithm for feature selection in Arabic sentiment analysis by Tubishat, Mohammad, Abushariah, Mohammad A.M., Idris, Norisma, Aljarah, Ibrahim

    Published 2019
    “…In addition, we also used Information Gain (IG) as a filter features selection technique with WOA using Support Vector Machine (SVM) classifier to reduce the search space explored by WOA. …”
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    Article
  14. 14

    Comparison for selection technique in genetic algorithm by Muhamad Azree, Mat Said

    Published 2006
    “…The purpose of this project is to make a comparison for three selection techniques in Genetic Algorithm.The Genetic Algorithm has been implemented in the previous module for Chess Tournament Management System.Base on previous system the selection method only using randomize.By this project module,only three selections method were use for the comparison.They are Roulette Wheel, Steady-State and Rank selection.The result for this comparison has determined the appropriate selection for Genetic Algorithm implementation in Chess Tournament Management System.This will help Chess Tournament Management System to provide a better optimize schedule.…”
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    Undergraduates Project Papers
  15. 15

    Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm by Nur Azulia, Kamarudin

    Published 2019
    “…In conclusion, SURE(IFGLS)-Autometrics and SURE(EM)-Autometrics can be used as models selection algorithms. Additionally, both algorithms are suitable in improving performance of automated models selection procedures. …”
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    Thesis
  16. 16

    SURE-Autometrics algorithm for model selection in multiple equations by Norhayati, Yusof

    Published 2016
    “…The SURE-Autometrics is also validated using two sets of real data by comparing the forecast error measures with five model selection algorithms and three non-algorithm procedures. …”
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    Thesis
  17. 17

    Statistical fixed range multiple selection algorithm for peer-to-peer system by Kweh, Yeah Lun, Othman, Mohamed, Ahmad, Fatimah, Ibrahim, Hamidah

    Published 2010
    “…In this research, a new multiple selection algorithm, which is known as "statistical fixed range multiple selection algorithm" is proposed. …”
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    Conference or Workshop Item
  18. 18

    Static range multiple selection algorithm for peer-to-peer system by Othman, Mohamed, Kweh, Yeah Lun, Ahmad, Fatimah, Ibrahim, Hamidah

    Published 2011
    “…In this research, a new multiple selection algorithm, which is known as "static range statistical multiple selection algorithm" is proposed. …”
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    Conference or Workshop Item
  19. 19

    Metaheuristic algorithms for feature selection (2014–2024) by Faizan, Muhammad, Muhammad Arif, Mohamad

    Published 2025
    “…Feature selection is a process used during machine learning and data analysis, aimed at selecting the best features to increase model efficiency, decrease complexity, and increase readability. …”
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    Article
  20. 20

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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    Thesis