Search Results - (( pattern (matching OR machine) algorithm ) OR ( patterns ((ant algorithm) OR (path algorithm)) ))

Refine Results
  1. 1

    Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…Support Vector Machines are considered to be excellent patterns classification techniques. …”
    Get full text
    Get full text
    Get full text
    Article
  2. 2

    Optimizing support vector machine parameters using continuous ant colony optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2012
    “…Support Vector Machines are considered to be excellent patterns classification techniques.The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and may be done experimentally through time consuming human experience.To overcome this difficulty, an approach such as Ant Colony Optimization can tune Support Vector Machine parameters.Ant Colony Optimization originally deals with discrete optimization problems. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  3. 3

    Destination prediction based on past movement history by Waheed, Mihsaan

    Published 2020
    “…In this paper we explore destination prediction using the past movement history, where the history is built using machine learning. Matching of the history with the user's movement is done through a simple pattern recognition technique. …”
    Get full text
    Thesis
  4. 4
  5. 5

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

    Published 2013
    “…Ant Colony Optimization (ACO) is a metaheuristic algorithm that can be used to solve a variety of combinatorial optimization problems. …”
    Get full text
    Get full text
    Get full text
    Thesis
  6. 6

    Traditional marble game using ant colony optimization / Muhammad Izzat Imran Che Isa by Che Isa, Muhammad Izzat Imran

    Published 2017
    “…In future, traditional marble game can be applied with other search algorithm to optimize the solution…”
    Get full text
    Get full text
    Thesis
  7. 7

    Ant colony algorithm for text classification in multicore-multithread environment / Ahmad Nazmi Fadzal by Fadzal, Ahmad Nazmi

    Published 2017
    “…Pheromone concept is the main criterion that distinguish ACO to other algorithms. Based on the concept, pheromone saturation is used to combine stackable solution pattern that is discovered while straying to different term node to build a path. …”
    Get full text
    Get full text
    Thesis
  8. 8

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

    Published 2016
    “…In future work, the accuracy of proposed model can be strengthened by comparative study with other heuristic based searching algorithms such as genetic algorithm, ant colony optimization, swam algorithms and etc.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  9. 9

    Machine learning using robust AI techniques / Prof. Madya Dr. Nordin Abu Bakar by Abu Bakar, Nordin (Prof. Madya Dr.)

    Published 2012
    “…Many algorithms have been applied to aid the assessment process. …”
    Get full text
    Get full text
    Research Reports
  10. 10

    Feature extraction: hand shape, hand position and hand trajectory path by Bilal, Sara Mohammed Osman Saleh, Akmeliawati, Rini

    Published 2011
    “…The performance of recognition system fIrst depends on the process of getting effIcient features to represent pattern characteristics [1]. There is no algorithm which shows how to select the representation or choose the features [2] so the selection of features will depend on the application. …”
    Get full text
    Get full text
    Get full text
    Book Chapter
  11. 11

    Local DTW coefficients and pitch feature for back-propagation NN digits recognition by Sudirman, R., Salleh, Shahruddin Hussain, Salleh, Sh-Hussain

    Published 2006
    “…The coefficients are normalized with respect to the reference pattern according to the average number of frames over the samples recorded. …”
    Get full text
    Conference or Workshop Item
  12. 12

    Local DTW Coefficients and Pitch Feature for Back-Propagation NN Digits Recognition by Sudirman, Rubita, Salleh, Sh-Hussain, Salleh, Shaharuddin

    Published 2006
    “…The coefficients are normalized with respect to the reference pattern according to the average number of frames over the samples recorded. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  13. 13
  14. 14

    Advances in materials informatics: A review by Sivan, Dawn, Kumar, K. Satheesh, Aziman, Abdullah, Raj, Veena, Izan Izwan, Misnon, Ramakrishna, Seeram, Jose, Rajan

    Published 2024
    “…Conventional ML models are simple and interpretable, relying on statistical techniques and algorithms to learn patterns and make predictions with limited data. …”
    Get full text
    Get full text
    Get full text
    Article
  15. 15

    A robust, scalable multi-robot control and coordination framework achieving high throughput for parcel sorting centers by Ch'ng, Chee Henn

    Published 2025
    “…The research demonstrates significant improvements in system throughput, with pattern-matching allocators outperforming native allocators by up to 23.52%. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  16. 16

    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
  17. 17

    Machine Learning Based Detection for Compromised Accounts on Social Media Networks by K., Swapna, M., Rithika, K., Rukmini, S., Swachitha, Y., Komali

    Published 2025
    “…Behavioral features include changes in posting frequency, interaction patterns, and location data. We employ machine learning algorithms to train models that can accurately classify accounts as compromised or legitimate based on these features. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  18. 18
  19. 19
  20. 20