Search Results - (( pattern generation process algorithm ) OR ( java application customization algorithm ))

Refine Results
  1. 1
  2. 2

    A numerical method for frequent pattern mining by Mustapha, Norwati, Nadimi-Shahraki, Mohammad-Hossein, Mamat, Ali, Sulaiman, Md. Nasir

    Published 2009
    “…Identifying all frequent patterns is the most time consuming process due to a massive number of patterns generated. …”
    Get full text
    Get full text
    Article
  3. 3
  4. 4

    Finger Vein Recognition Using Pattern Map As Feature Extraction by Teoh, Saw Beng

    Published 2012
    “…Instead of obtaining fmger vein features from multi-filtered images, the features images are generated from pattern templates which are the eigenveins obtained from PCA process. …”
    Get full text
    Get full text
    Thesis
  5. 5

    Performance of IF-Postdiffset and R-Eclat Variants in Large Dataset by Julaily Aida, Jusoh, Wan Aezwani, Wan Abu Bakar, Mustafa, Man

    Published 2018
    “…The multiple variants in the R-Eclat algorithm generate varied performances in infrequent mining patterns. …”
    Get full text
    Get full text
    Article
  6. 6

    Development of automated neighborhood pattern sensitive fault syndrome generator for SRAM by Rusli, Julie Roslita, Mohd Sidek, Roslina, Wan Hasan, Wan Zuha

    Published 2012
    “…A proven March algorithms are used in this generator to verify the efficiency of this generator by producing the fault coverage and diagnostic resolution. …”
    Get full text
    Get full text
    Conference or Workshop Item
  7. 7

    Exploring High Resolution Test Pattern To Improve The Cache Failure Analysis by Ong, Chein Ee

    Published 2017
    “…The generated high resolution test pattern is integrated for Automated Test Equipment (ATE) usage so that the test pattern can be applied in real silicon device testing. …”
    Get full text
    Get full text
    Thesis
  8. 8

    Discovering Pattern in Medical Audiology Data with FP-Growth Algorithm by G. Noma, Nasir, Mohd Khanapi, Abd Ghani

    Published 2012
    “…We use frequent pattern growth (FP-Growth) algorithm in the data processing step to build the FP-tree data structure and mine it for frequents itemsets. …”
    Get full text
    Get full text
    Conference or Workshop Item
  9. 9

    Automatic generation of user-defined test algorithm description file for memory BIST implementation by Hussin, Razaidi, Jidin, Aiman Zakwan, Loh, Wan Ying, Mispan, Mohd Syafiq, Lee, Weng Fook

    Published 2022
    “…The proposed automation software was tested by using March SR as the input algorithm and the results obtained from the simulations show that the output test patterns generated by the implemented memory BIST match the expected patterns and passed all the tests, which validated the correct functionality of the UDA description file generation. …”
    Get full text
    Get full text
    Get full text
    Article
  10. 10

    Application of genetic algorithm and JFugue in an evolutionary music generator by Tang, Jia Rou

    Published 2025
    “…This project explores the application of Genetic Algorithms (GA) with JFugue, which is a Java-based music programming library to develop an Evolutionary Music Generator. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  11. 11

    Optimizing Central Pattern Generators (CPG) Controller For One Legged Hopping Robot By Using Genetic Algorithm (GA) by Chong, Shin Horng, Azahar, Arman Hadi, Mohamed Kassim, Anuar, Zainal Abidin, Amar Faiz, Harun, Mohamad Haniff, Nor Shah, Mohd Badril, Mohd Annuar, Khalil Azha, Manap, Mustafa, Rizman, Zairi Ismael

    Published 2018
    “…This paper presents the optimization process of Central Pattern Generator (CPG) controller for one legged hopping robot by using Genetic Algorithm (GA).To control the one legged hopping robot,a CPG controller is designed and integrated with a conventional ProportionalIntegral (PI) controller.Conventionally,the CPG parameters are tuned manually.But by using this method,the parameters produced are not exactly the optimum parameters for the CPG. …”
    Get full text
    Get full text
    Get full text
    Article
  12. 12

    MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, khan

    Published 2011
    “…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data.…”
    Get full text
    Get full text
    Citation Index Journal
  13. 13

    MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, Khan

    Published 2011
    “…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data.…”
    Get full text
    Get full text
    Citation Index Journal
  14. 14

    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. …”
    Get full text
    Get full text
    Thesis
  15. 15

    Frequent patterns minning of stock data using hybrid clustering association algorithm by B., Baharudin, A., Khan, K., Khan

    Published 2009
    “…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  16. 16

    A filtering algorithm for efficient retrieving of DNA sequence by Abdul Rahman, Mohd Nordin, Mohd. Saman, Md. Yazid, Ahmad, Aziz, Md. Tap, Abu Osman

    Published 2009
    “…Heuristics algorithms can process a fast DNA sequence alignment, but generate low comparison sensitivity. …”
    Get full text
    Get full text
    Get full text
    Article
  17. 17

    Pattern generation through feature values modification and decision tree ensemble construction by Akhand, M. A. H, Rahman, M.M. Hafizur, Murase, K.

    Published 2013
    “…The method modifies feature values of some patterns with the values of other patterns to generate different patterns for different classifiers. …”
    Get full text
    Get full text
    Get full text
    Article
  18. 18

    Comparison between Market Basket Analysis and Partition Around Medoids clustering for knowledge discovering in consumer consumption pattern / Mohammad Adha Ruslan, Nurul Shahira Mo... by Ruslan, Mohammad Adha, Mohammad Ramly, Nurul Shahira, Saberi, Nor Hasliza

    Published 2019
    “…The main purpose of this study are to compare the knowledge discovery between Market Basket Analysis and Partition Around Medoids and followed by to generate a customer buying pattern by using Market Basket Analysis (MBA) Algorithm and Partition Around Medoids (PAM) Clustering Algorithm. …”
    Get full text
    Get full text
    Student Project
  19. 19

    Developing triad design algorithms based on compatible factorization by Ibrahim, Haslinda, Omar, Zurni, Abdul Rahim, Rahela

    Published 2011
    “…We consider the problem of listing distinct triples that satisfy certain properties.This problem is known as triad design of order v; TD(v).This design exists for v = 1 or 5 (mod v).Much of our work deals with the enumeration of several triad design, for example TD(7); TD(11) and TD(13). These processes have helped us develop algorithm for triad design, the objective of this study.A new technique for triad design algorithm, known as Interval Generation Method was employed to construct TD(6n + 1) and TD(6n + 5).This method depends on analyzing the pattern of triples in the design to build starters.We begin by producing starters from Interval Generation Method as the initial block to begin with.Then the algorithm begins by cycling modular v from the initial block and finishes when the process approaches the initial block.The algorithms for TD(6n+1) and TD(6n+5) are presented in Chapter 4 and 5, respectively.As the entire study depends mainly on TD(v) algorithms, new and remarkable theorems and lemmas for TD(v) development are presented and proved.…”
    Get full text
    Get full text
    Get full text
    Monograph
  20. 20