Search Results - (( pattern based algorithm ) OR ((( between working algorithm ) OR ( e learning algorithm ))))

Refine Results
  1. 1

    Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

    Published 2021
    “…However, less works have been conducted in applying multiobjective based algorithm for topic extraction. …”
    Get full text
    Get full text
    Article
  2. 2
  3. 3

    Application of machine learning and artificial intelligence in detecting SQL injection attacks by Md Sultan, Abu Bakar, Agiliga, Nwabudike Augustine, Osman, Mohd Hafeez Bin, Sharif, Khaironi Yatim

    Published 2024
    “…Datasets of well-known SQL injection attack patterns and AI/ML models intended for cybersecurity anomaly detection are among the resources underexplored, these findings show the potential for boosting detection capabilities by deploying ML and AI-based security solutions, with some algorithms scoring up to an 80 percent success rate in identifying SQL injections. …”
    Get full text
    Get full text
    Get full text
    Article
  4. 4

    Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

    Published 2023
    Subjects: “…Knuth-Morris-Pratt (KMP) pattern matching algorithm…”
    Conference paper
  5. 5

    Raspberry Pi-Based Finger Vein Recognition System Using PCANet by Quek, Ee Wen

    Published 2018
    “…For classification, k-Nearest Neighbours (kNN) with Euclidean distance algorithm is implemented. An enhancement version for kNN algorithm, k-General Nearest Neighbours (kGNN) have been proposed at initial stage. …”
    Get full text
    Get full text
    Monograph
  6. 6

    Lexicon-based and immune system based learning methods in Twitter sentiment analysis by Jantan, Hamidah, Drahman, Fatimatul Zahrah, Alhadi, Nazirah, Mamat, Fatimah

    Published 2016
    “…The aim of this article attempts to study the potential of this method in text classification for sentiment analysis.This study consists of three phases; data preparation; classification model development using three selected Immune System based algorithms i.e. Negative Selection algorithm (NSA), Clonal Selection algorithm (CSA) and Immune Network algorithm (INA); and model analysis. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  7. 7

    Market prices trend forecasting supported by Elliott Wave's theory by Vantuch, T., Zelinka, I., Vasant, P.

    Published 2017
    “…The trend prediction is supported by application of recognized Elliot waves which was performed by custom developed algorithm based on available knowledge about the patterns. …”
    Get full text
    Get full text
    Article
  8. 8

    Web usage mining for UUM learning care using association rules by Ramli, Azizul Azhar

    Published 2004
    “…In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. …”
    Get full text
    Get full text
    Thesis
  9. 9

    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

    Published 2006
    “…Traditional schema theory does not support Lamatckian learning, i.e, forcing the genetic representation to match the solution found by the learning algorithm. …”
    Get full text
    Get full text
    Get full text
    Article
  10. 10

    Web Usage Mining for UUM Learning Care Using Association Rules by Azizul Azhar, Ramli

    Published 2004
    “…In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. …”
    Get full text
    Get full text
    Get full text
    Thesis
  11. 11

    The development of an automated pattern recognition based on neural network / Irni Hamiza Hamzah, Mohammad Nizam Ibrahim and Linda Mohd Kasim by Hamzah, Irni Hamiza, Ibrahim, Mohammad Nizam, Mohd Kasim, Linda

    Published 2006
    “…The capability of powerful personal computers and affordable and high resolution sensors (i.e.: CCD cameras, microphones and scanners) have fostered the development of pattern recognition algorithms in new application domains (i.e.: fuzzy logic, neural network and genetic algorithm). …”
    Get full text
    Get full text
    Research Reports
  12. 12
  13. 13
  14. 14

    Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks by F. M., Mohammed

    Published 2014
    “…Two enhanced FMM variants, i.e. EFMM and EFMM2, are proposed to address a number of limitations in the original FMM learning algorithm. …”
    Get full text
    Get full text
    Thesis
  15. 15

    Fish Motion Trajectories Detection Algorithm Based on Spiking Neural Network (S/O: 12893) by Yusoff, Nooraini, Yusof, Yuhanis, Siraj, Fadzilah, Ahmad, Farzana Kabir

    Published 2017
    “…The significant contribution for this study is that the learning rule (e.g. STDP algorithm) has learning capability in memory recall. …”
    Get full text
    Get full text
    Monograph
  16. 16
  17. 17
  18. 18
  19. 19

    Scrutinized System Calls Information Using J48 And Jrip For Malware Behaviour Detection by Abdollah, Mohd Faizal, S. M. M Yassin, S. M. Warusia Mohamed, Mohd Saudi, Nur Hidayah

    Published 2019
    “…This integrated classifier algorithm applied to analyse, classify and generate rules of the pattern and program behaviour of system call information in which, the legal and illegal behaviours could identify. …”
    Get full text
    Get full text
    Get full text
    Article
  20. 20

    Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Chong, Hou Ming, Yin Yap, Xien, Seng Chia, Kim

    Published 2023
    “…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. Five different pre-trained deep learning algorithms (i.e. …”
    Get full text
    Get full text
    Get full text
    Article