Search Results - (( data classification matching algorithm ) OR ( evolution optimization parallel algorithm ))

Refine Results
  1. 1

    Optimization of extractive Automatic Text Summarization using Decomposition-based Multi-objective Differential Evolution and parallelization by Hazmi Wahab, Muhammad Hafizul

    Published 2024
    “…The central challenge in Automatic Text Summarization (ATS) is efficiently generating machine-generated text summaries through optimization algorithms, a critical component for systems dealing with textual information processing. …”
    Get full text
    Get full text
    Get full text
    Thesis
  2. 2

    Improving sentiment reviews classification performance using support vector machine-fuzzy matching algorithm by Nurcahyawati, Vivine, Mustaffa, Zuriani

    Published 2023
    “…High dimensionality in data sets is one of the challenges faced in classification, data mining, and sentiment analysis. …”
    Get full text
    Get full text
    Get full text
    Article
  3. 3

    Trademark image classification approaches using neural network and rough set theory by Saad, Puteh

    Published 2003
    “…The approaches contain five major stages, namely: image acquisition, image preprocessing, feature extraction, data transformation and classification. Feature normalization and data discretization techniques are utilized to perform the data transformation phase. …”
    Get full text
    Get full text
    Get full text
    Thesis
  4. 4

    Converged Classification Network For Matching Cost Computation by Hamid, Mohd Saad, Abd Manap, Nurulfajar, Hamzah, Rostam Affendi, Kadmin, Ahmad Fauzan

    Published 2020
    “…The stereo matching algorithm capable of producing the disparity or depth map in computer. …”
    Get full text
    Get full text
    Get full text
    Article
  5. 5

    PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

    Published 2020
    “…To evaluate the PMT’s performance and adaptability, the PMT was applied to four contemporary metaheuristic algorithms, Differential Evolution, Particle Swarm Optimization, Simulated Annealing, and Whale Optimization Algorithm, to solve 15 well-known benchmark functions as well as 2 real world problems based on the welded beam design and pressure vessel design. …”
    Get full text
    Get full text
    Thesis
  6. 6

    PMT: opposition-based learning technique for enhancing meta-heuristic performance by Alamri, Hammoudeh S., Kamal Z., Zamli

    Published 2019
    “…To evaluate the PMT's performance and adaptability, the PMT has been applied to four contemporary meta-heuristic algorithms, differential evolution (DE), particle swarm optimization (PSO), simulated annealing (SA), and whale optimization algorithm (WOA), to solve 15 well-known benchmark functions. …”
    Get full text
    Get full text
    Get full text
    Article
  7. 7

    OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM by WAHYUNGGORO, OYAS WAHYUNGGORO

    Published 2011
    “…In this thesis, a new optimization GA-based algorithm that emanates from modification of conventional GA to reduce the iterations number and the duration time, namely, semi-parallel operation genetic algorithm (SPOGA) is proposed. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  8. 8

    Application Of Genetic Algorithms For Robust Parameter Optimization by Belavendram, N.

    Published 2010
    “…Genetic algorithms (GA) are fairly recent in this respect but afford a novel method of parameter optimization. …”
    Get full text
    Get full text
    Article
  9. 9

    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2011
    “…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  10. 10

    Training data selection for record linkage classification by Zaturrawiah Ali Omar, Zamira Hasanah Zamzuri, Noratiqah Mohd Ariff, Mohd Aftar Abu Bakar

    Published 2023
    “…The top and imbalanced construction was found to be the most effective in producing training data with 100% correct labels. Random forest and support vector machine classification algorithms were compared, and random forest with the top and imbalanced construction produced an F1 -score comparable to probabilistic record linkage using the expectation maximisation algorithm and EpiLink. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  11. 11

    A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

    Published 2002
    “…Rough sets theory represents a mathematical approach to vagueness and uncertainty. Data analysis, data reduction, approxi mate classification, machine learning, and discovery of pattern in data are functions performed by a rough sets analysis. …”
    Get full text
    Get full text
    Thesis
  12. 12

    An Ar Natural Marker Similarities Measurement Algorithm For E-Biodiversity by Tan, Mei Synn, Wang, Yin Chai

    Published 2018
    “…Algorithms of investigation starting with span from extraction, matching and classification to determine the interest point of flower species, like colour and shape features information. …”
    Get full text
    Get full text
    Proceeding
  13. 13
  14. 14

    Non-fiducial based electrocardiogram biometrics with kernel methods by Hejazi, Maryamsadat

    Published 2017
    “…The lowest biometric errors of false non-match rate and false match rate are decreased to about 6.19% and 1.79%, respectively on the KPCA data set.…”
    Get full text
    Get full text
    Thesis
  15. 15

    A comparative study in classification techniques for unsupervised record linkage model by Ektefa, Mohammadreza, Sidi, Fatimah, Ibrahim, Hamidah, A. Jabar, Marzanah, Memar, Sara

    Published 2011
    “…In order to utilize the supervised classification algorithms without consuming a lot of time for labeling data manually, a two step method which selects the training data automatically has been proposed in previous studies. …”
    Get full text
    Get full text
    Get full text
    Article
  16. 16

    A new hybrid technique for nosologic segmentation of primary brain tumors / Shafaf Ibrahim by Ibrahim, Shafaf

    Published 2015
    “…It is designed to incorporate with the CAPSOCA algorithm which intended to strengthen the classification outcomes. …”
    Get full text
    Get full text
    Thesis
  17. 17

    AUTONOMOUS MOBILE ROBOT VISION BASED SYSTEM: HUMAN DETECTION BY COLOR by Mohd Shah, Hairol Nizam, Ab Rashid, Mohd Zamzuri, Mohd Sobran, Nur Maisarah

    Published 2013
    “…Then classification algorithm is applied to find the centroid of the human. …”
    Get full text
    Get full text
    Article
  18. 18
  19. 19

    Improved GART neural network model for pattern classification and rule extraction with application to power systems by Yap K.S., Lim C.P., Au M.T.

    Published 2023
    “…IGART enhances the dynamics of GART in several aspects, which include the use of the Laplacian likelihood function, a new vigilance function, a new match-tracking mechanism, an ordering algorithm for determining the sequence of training data, and a rule extraction capability to elicit if-then rules from the network. …”
    Article
  20. 20