Search Results - (( using normalization _ algorithm ) OR ( data classification based algorithm ))

Refine Results
  1. 1

    Classification of Cardiac Disorders Based on Electrocardiogram Data with Fuzzy Cognitive Map (FCM) Algorithm Approach by Sumiati, ., Hoga, Saragih, T.K.A, Rahman, Viktor Vekky, Ronald Repi, Agung, Triayudi

    Published 2021
    “…This research contributes to the world of health, where we classify the Electrocardiogram (ECG) data, so that it can classify abnormal and normal cardiac disorders using the Fuzzy Cognitive Map (FCM) algorithm.…”
    Get full text
    Get full text
    Conference or Workshop Item
  2. 2

    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

    Published 2018
    “…There are two stages in the proposed classification system. Firstly, the 1D-LBP algorithm is used to extract the features of the normalized iris images and save the data in a text file according to the subject and the combinations to evaluate for the next stage. …”
    Get full text
    Get full text
    Monograph
  3. 3

    Development of classification model between clean water and polluted water based on capacitance properties using Levenberg Marquardt (LM) algorithm of artificial neural network / M... by Mohamad Salehuddin, Mohamad Firdaus

    Published 2020
    “…These measurement inputs were then going through the process of classification in ANN to generate the optimized models by using LM algorithm. …”
    Get full text
    Get full text
    Student Project
  4. 4

    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

    Published 2019
    “…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
    Get full text
    Get full text
    Thesis
  5. 5

    An efficient algorithm for cardiac arrhythmia classification using ensemble of depthwise Separable convolutional neural networks by Ihsanto, Eko, Ramli, Kalamullah, Sudiana, Dodi, Gunawan, Teddy Surya

    Published 2020
    “…Using only these 22% labeled training data, our proposed algorithm was able to classify the remaining 78% of the database into 16 classes. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  6. 6

    Spectral discrimination and index development of roofing materials and conditions using field spectroscopy and worldview-3 satellite image by Samsudin, Sarah Hanim

    Published 2016
    “…The classification accuracy using spectral indices were compared with the normal supervised pixel-based classification of SVM. …”
    Get full text
    Get full text
    Thesis
  7. 7

    Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors by AlRijeb, Mothena Fakhri Shaker, Othman, Mohammad Lutfi, Ishak, Aris, Hassan, Mohd Khair, Albaker, Baraa Munqith

    Published 2025
    “…One of the powerful optimization algorithms that is used for feature selection is the Whale Optimization Algorithm (WOA), which is a nature-inspired metaheuristic optimization algorithm that mimics the social behavior of humpback whales. …”
    Get full text
    Get full text
    Get full text
    Article
  8. 8

    Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks by Abualsaud, Khalid, Mahmuddin, Massudi, Saleh, Mohammad, Mohamed, Amr

    Published 2014
    “…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  9. 9

    Classification of fault and stray gassing in transformer by using duval pentagon and machine learning algorithms by Haw, Jia Yong, Mohd Yousof, Mohd Fairouz, Abd Rahman, Rahisham, Talib, Mohd Aizam, Azis, Norhafiz

    Published 2022
    “…The algorithms that will be used include boosted trees, RUS boosted trees and subspace KNN, which belongs to the same ensemble group. …”
    Get full text
    Get full text
    Article
  10. 10

    Monitoring the impacts of drought on land use/cover: a developed object-based algorithm for NOAA AVHRR time series data by Mokhtari, Ahmad, Mansor, Shattri, Mahmud, Ahmad Rodzi, Mohd Shafri, Helmi Zulhaidi

    Published 2011
    “…As a novel idea in this study, it developed a new object-based classification algorithm for AVHRR (Advanced Very High Resolution Radiometer) data. …”
    Get full text
    Get full text
    Get full text
    Article
  11. 11
  12. 12

    Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

    Published 2009
    “…The SNS classification model use negative selection and PSO algorithms to form a set of memory Artificial Lymphocytes (ALCs) that have the ability to distinguish between normal and epileptic EEG patterns. …”
    Get full text
    Article
  13. 13

    A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island by Mohd Shafri, Helmi Zulhaidi, Ramle, F. S. H.

    Published 2009
    “…The study indicates that the classification accuracy of SVM algorithm was better than DT algorithm. The overall accuracy of the SVM using four kernel types was above 73% and the overall accuracy of the DT method was 69%. …”
    Get full text
    Get full text
    Get full text
    Article
  14. 14

    SVM for network anomaly detection using ACO feature subset by Mehmood, T., Rais, H.B.M.

    Published 2016
    “…Classification approach has been widely adopted for the development of the anomaly detection model to classify the data into normal class and attack class. …”
    Get full text
    Get full text
    Conference or Workshop Item
  15. 15
  16. 16

    Artificial immune system based on real valued negative selection algorithms for anomaly detection by Khairi, Rihab Salah

    Published 2015
    “…The Real-Valued Negative Selection Algorithms, which are the focal point of this research, generate their detector sets based on the points of self data. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  17. 17

    Automatic Classification of Cervix Type by Muktiar Singh, Jasdeep Singh

    Published 2019
    “…Due to that, in this study, few algorithms were developed by using image classification methods to correctly classify the cervix types based on cervical images by using segmentation and classification method. …”
    Get full text
    Get full text
    Final Year Project
  18. 18

    Effective gene selection techniques for classification of gene expression data by Yeo, Lee Chin

    Published 2005
    “…Various k-means clustering algorithms and model-based clustering algorithms are proposed to group the genes. …”
    Get full text
    Get full text
    Thesis
  19. 19

    Pengkelasan Sel Kanser Pangkal Rahim Kepada Sel Normal Dan Tidak Normal Menggunakan Analisis Pembezalayan Dan Rangkaian Neural by Saidin, Mohammad Norrish

    Published 2006
    “…The topic of this project is classification of cervical cells into normal and abnormal using 2 group discriminant analysis and neural network. …”
    Get full text
    Get full text
    Monograph
  20. 20

    EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter by Woon, W.C., Yahya, N., Badruddin, N.

    Published 2019
    “…Hence, this work aims to develop an algorithm using statistical-CSP feature for eye state classification from EEG signal. …”
    Get full text
    Get full text
    Conference or Workshop Item