Search Results - (( (variable OR variables) selection process algorithm ) OR ( java application using algorithm ))

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  1. 1

    Message based random variable length key encryption algorithm. by Mirvaziri, Hamid, Jumari, Kasmiran, Ismail, Mahamod, Mohd Hanapi, Zurina

    Published 2009
    “…None fixed size key caused avoidance of replaying and other attacks that can happen on fixed sized key algorithms. Conclusion: Random process employed in this block cipher increased confidentiality of the message and dynamic length substitution in proposed algorithm may lead to maximum cryptographic confusion and consequently makes it difficult for cryptanalysis.…”
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    Article
  2. 2

    Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique by Hardev Singh, Jitvinder Dev Singh

    Published 2015
    “…The variable block matching developed based on four stages which is the video and frame selection, threshold calculation, block size selection and search pattern. …”
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    Thesis
  3. 3

    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2025
    “…An experimental study was conducted, and the variable selection process using the normalization-based Binary Bat algorithm found a better combination of input variables which consists of only six out of eight variables. …”
    Conference paper
  4. 4

    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…The significance of the selected input variable vectors is studied to analyze their effects on the prediction process. …”
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    Article
  5. 5

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

    Published 2016
    “…This automatic model selection algorithm is better than non-algorithm procedure which requires knowledge and extra time. …”
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    Thesis
  6. 6

    Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition by Yahya, Anwar Ali, Mahmod, Ramlan, Ramli, Abd Rahman

    Published 2010
    “…In the second stage, the developed variable length genetic algorithm is used to select different sets of lexical cues to constitute the dynamic Bayesian networks' random variables. …”
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    Article
  7. 7

    Mixed variable ant colony optimization technique for feature subset selection and model selection by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…This paper presents the integration of Mixed Variable Ant Colony Optimization and Support Vector Machine (SVM) to enhance the performance of SVM through simultaneously tuning its parameters and selecting a small number of features.The process of selecting a suitable feature subset and optimizing SVM parameters must occur simultaneously,because these processes affect each ot her which in turn will affect the SVM performance.Thus producing unacceptable classification accuracy.Five datasets from UCI were used to evaluate the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with the small size of features subset.…”
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    Conference or Workshop Item
  8. 8

    New selection algorithm for Mengubah Destini Anak Bangsa (MDAB) students / Zamali Tarmudi ... [et al.] by Tarmudi, Zamali, Saibin, Tammie Christy, Naharu, Nasrah, Ung, Ling Ling

    Published 2014
    “…It focuses on the refinement and modification of certain variables in selection process. The technique employs the intersection of fuzzy goals and constraints concept in judgmental process. …”
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    Research Reports
  9. 9

    Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition by Ali Yahya, Anwar

    Published 2007
    “…In the selection phase, a new variable length genetic algorithm is applied to select the lexical cues. …”
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    Thesis
  10. 10

    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification by Abd Samad, Md Fahmi

    Published 2011
    “…Model structure selection is one of the important steps in a system identification process. …”
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    Article
  11. 11

    Fault diagnostic algorithm for precut fractionation column by Heng, H. Y., Ali, Mohamad Wijayanuddin, Kamsah, Mohd. Zaki

    Published 2004
    “…The fault diagnostic algorithm is supported by the process history based method and developed by using Borland C++ Builder 6.0. …”
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    Conference or Workshop Item
  12. 12

    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
  13. 13

    Penalized Quantile Regression Methods And Empirical Mode Decomposition For Improving The Accuracy Of The Model Selection by Ambark, Ali Saleh Al-Massri

    Published 2024
    “…In several studies, these components have been employed as novel predictor variables to study the behaviour of the response variable. …”
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    Thesis
  14. 14

    Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC) by Ibrahim, Kamarul 'Asri, Ahmad, Arshad, Ali, Mohamad Wijayanuddin, Mak, Weng Yee

    Published 2006
    “…In this research work, an FDD algorithm is developed using MSPC and correlation coefficients between process variables. …”
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    Monograph
  15. 15

    Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio... by Daba, Layth Muwafaq Abdulhussein

    Published 2023
    “…Unlike the existing optimization algorithm, VL-WIDE features the capability of searching different lengths of solutions to cover the variable number of cloudlets for deployment. …”
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    Thesis
  16. 16

    Development Of Fall Risk Clustering Algorithm In Older People by Wong, Kam Kang

    Published 2020
    “…The proposed algorithm consists of several stages, includes data pre-processing, feature selection, feature extraction, clustering and characteristic interpretation. …”
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    Final Year Project / Dissertation / Thesis
  17. 17

    Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

    Published 2013
    “…This is achieved by performing the SVM parameters’ tuning and feature subset selection processes simultaneously. Hybridization algorithms between ACO and SVM techniques were proposed. …”
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    Thesis
  18. 18

    Strategies of Handling Different Variables Reduction for LDA by Hamid, Hashibah, Mahat, Nor Idayu

    Published 2012
    “…The variables selection technique with local searching algorithm is manipulated. …”
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    Article
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    Application of Decision Trees in Athlete Selection: A Cart Algorithm Approach by Riska Wahyu, Romadhonia, A'yunin, Sofro, Danang, Ariyanto, Dimas Avian, Maulana, Junaidi Budi, Prihanto

    Published 2023
    “…Notably, weight, and Body Mass Index (BMI) exhibit the highest significance among the other variables. Looking ahead, future research could explore enhancing DTs' predictive capabilities in athlete selection by incorporating more variables or employing ensemble learning techniques. …”
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    Article