Search Results - (( using optimization approach algorithm ) OR ( pattern selection based algorithm ))

Refine Results
  1. 1

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

    Published 2023
    “…The main objective of this paper is to propose and implement an intelligent framework documentation approach that integrates case-based learning (CBL) with genetic algorithm (GA) and Knuth-Morris-Pratt (KMP) pattern matching algorithm with the intention of making learning a framework more effective. …”
    Conference paper
  2. 2

    Improving explicit aspects extraction in sentiment analysis using optimized ruleset / Mohammad Ahmad Jomah Tubishat by Mohammad Ahmad, Jomah Tubishat

    Published 2019
    “…In addition, extraction rules including either pattern-based or dependency-based rules should be selected in a correct way to remove the irrelevant rules and minimize the extraction errors Thus, in this study, to select the most effective extraction rules, an improved version of Whale Optimization Algorithm (IWOA) is developed and applied to a full set of rules. …”
    Get full text
    Get full text
    Get full text
    Thesis
  3. 3

    Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin by Shamsudin, Farah Syadiyah

    Published 2017
    “…Therefore, the aim for this project is to develop a new approach in the fingerprint verification system by applying Clonal Selection Algorithm (CSA) that is known to be good in pattern matching and optimization of problems. …”
    Get full text
    Get full text
    Thesis
  4. 4

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

    Published 2016
    “…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
  5. 5

    Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification by Prathama, Y.B.H., Shapiai, M.I., Aris, S.A.M., Ibrahim, Z., Jaafar, J., Fauzi, H.

    Published 2017
    “…In this paper, we propose an algorithm called Feature Scaling Common Spatial Pattern (FSc-CSP) to overcome the problem of feature selection. …”
    Get full text
    Get full text
    Article
  6. 6
  7. 7

    A multi-objective evolutionary approach for fuzzy optimization in production planning by P., Vasant, F., Jimenez, G., Sanchez, J.L., Verdegay

    Published 2007
    “…An ad hoc Pareto-based multi-objective evolutionary algorithm is proposed to capture multiple non dominated solutions in a single run of the algorithm. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  8. 8

    Efficient gear fault feature selection based on moth‑flame optimisation in discrete wavelet packet analysis domain by Ong, Pauline, Tieh, Tony Hieng Cai, Lai, Kee Huong, Lee, Woon Kiow, Ismon, Maznan

    Published 2019
    “…For this purpose, this study used the intensification and diversification properties of the recently proposed moth-flame optimisation (MFO) algorithm and utilised the algorithm in the proposed feature selection scheme. …”
    Get full text
    Get full text
    Get full text
    Article
  9. 9

    An efficient model for indoor radio signal prediction and coverage estimation / Md. Sumon Sarker by Md. Sumon, Sarker

    Published 2011
    “…It minimizes the number of transmitters in the corresponding indoor area using a novel integrated approach of the proposed ray-tracing and genetic algorithm (GA). …”
    Get full text
    Get full text
    Thesis
  10. 10

    Improving neural networks training using experiment design approach by Chong, Wei Kean

    Published 2005
    “…Randomly select the m data set for conventional training algorithm. …”
    Get full text
    Get full text
    Thesis
  11. 11

    P300 detection of brain signals using a combination of wavelet transform techniques by Motlagh, Farid Esmaeili

    Published 2012
    “…By using three level of channel reduction, three subgroups of channels with the number of 17, 9, and 5 have been chosen based on their ability in P300 pattern recognition. …”
    Get full text
    Get full text
    Thesis
  12. 12

    Prediction of COVID-19 outbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman by Mohd Azman, Muhammad Qayyum

    Published 2024
    “…This research significantly contributes to the understanding of machine learning applications in the context of COVID-19 outbreak prediction, emphasizing the importance of algorithm and configuration selections for robust forecasting. …”
    Get full text
    Get full text
    Thesis
  13. 13

    Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients by Moghbel, Mehrdad

    Published 2017
    “…This is followed by the clustering of the liver tissues using particle swarm optimized spatial FCM algorithm. …”
    Get full text
    Get full text
    Get full text
    Thesis
  14. 14

    FACE CLASSIFICATION FOR AUTHENTICATION APPROACH BY USING WAVELET TRANSFORM AND STATISTICAL FEATURES SELECTION by DAWOUD JADALAH, NADIR NOURAIN

    Published 2011
    “…Two of them based on pattern (template) Matching Approach, and the other based on clustering approach. …”
    Get full text
    Get full text
    Thesis
  15. 15

    Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

    Published 2018
    “…Therefore, this was not incorporated in BBN models. Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
    Get full text
    Get full text
    Thesis
  16. 16

    Enhancing land cover classification in remote sensing imagery using an optimal deep learning model by Motwake, Abdelwahed, Hassan Abdalla Hashim, Aisha, Obayya, Marwa, Eltahir, Majdy M.

    Published 2023
    “…The current study presents an Improved Sand Cat Swarm Optimization with Deep Learning-based Land Cover Classification (ISCSODL-LCC) approach on the RSIs. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  17. 17

    Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment by Sojodishijani, Omid

    Published 2011
    “…In this thesis, an optimal transformation matrix is used to transform the time-labeled instances from original space to a new feature space in order to maximize the probability of selecting the correct class label for incoming instance by similarity-based classifiers. …”
    Get full text
    Get full text
    Thesis
  18. 18

    Ensemble learning using multi-objective optimisation for arabic handwritten words by Ghadhban, Haitham Qutaiba

    Published 2021
    “…It is designated as the Random Subset based Parents Selection (RSPS-NSGA-II) to handle neurons and accuracy. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  19. 19

    Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

    Published 2025
    “…The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
    Get full text
    Get full text
    Thesis
  20. 20

    Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis by Rochin Demong, Nur Atiqah, Mohamed Razali, Murni Zarina, Kamaruddin, Juliana Noor, Shamsuddin, Sazwan, Awang, Nor Ain, Kamarudin, Norjuliatie, Wan Othman, Noor Faradilla

    Published 2025
    “…Furthermore, classification using the Random Forest algorithm depicted that a 95.3% accuracy (k=0.768), confirming robust predictive capability in identifying course approval status and demand trends. …”
    Get full text
    Get full text
    Get full text
    Article