Search Results - (( data internalization based algorithm ) OR ( parameter detection method algorithm ))

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  1. 1

    Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

    Published 2021
    “…The NTLBO was proposed in this paper as an FSS mechanism; its algorithm-specific, parameter-less concept (which requires no parameter tuning during an optimization) was explored. …”
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    Article
  2. 2

    The multiple outliers detection for circular univariate data using different agglomerative clustering algorithms by Nur Syahirah, Zulkipli, Siti Zanariah, Satari, Wan Nur Syahidah, Wan Yusoff

    Published 2024
    “…Meanwhile, SL-Satari/Di, CL-Satari/Di, and AL-Satari/Di algorithms are recommended to be used for large sample sizes since these algorithms perform very well in detecting the outliers and have low masking and swamping effect at any percentage of outliers and concentration parameter. …”
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    Conference or Workshop Item
  3. 3

    Detection of the spread of Covid-19 in Indonesia using K-Means Clustering Algorithm / Mohammad Yazdi Pusadan ... [et al.] by Pusadan, Mohammad Yazdi, Rabbani, Mohammad Abied, Ardiansyah, Rizka, Ngemba, Hajra Rasmita

    Published 2023
    “…The purpose of this study is to apply the K-Means algorithm to perform clustering on COVID-19 data to determine the high spread of the virus in regions in Indonesia based on the frequency of the data. …”
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    Book Section
  4. 4

    A fast learning network with improved particle swarm optimization for intrusion detection system by Ali, Mohammed Hasan

    Published 2019
    “…However, the internal power parameters (weight and basis) of FLN are initialized at random, causing the algorithm to be unstable. …”
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    Thesis
  5. 5

    Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

    Published 2021
    “…Recently, deep learning methods have significantly sharpened the cutting edge of learning algorithms in a wide range of artificial intelligence tasks. …”
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    Article
  6. 6

    Defect recognition method for magnetic leakage detection in oil and gas steel pipes based on improved neural networks by Wang Jie, Mohd. Kamal Mohd. Shah, Choong Wai Heng, Nahiyan Al-Azad

    Published 2024
    “…Traditional BP networks face challenges, including parameter determination and slow convergence, addressed through genetic algorithms' global search capabilities. …”
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    Article
  7. 7

    Embedded Fuzzy Classifier for Detection and Classification of Preseizure State Using Real EEG Data by Qidwai, Uvais, Malik, Aamir Saeed, Shakir, Mohamed

    Published 2013
    “…However, the common clinical methods are insufficient when it comes to design an automated module to detect and predict partial seizure for epileptic patients. …”
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    Book Section
  8. 8

    Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data by Qidwai, U., Malik, A.S., Shakir, M.

    Published 2014
    “…Electroencephalography (EEG) plays an important role, especially EEG based health diagnosis of brain disorder. However, the common clinical methods are insufficient when it comes to design an automated module to detect and predict partial seizure for epileptic patients. …”
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    Conference or Workshop Item
  9. 9

    Federated deep learning for automated detection of diabetic retinopathy by Zainal Abidin, Nadzurah, Ismail, Amelia Ritahani

    Published 2022
    “…Deep learning is a machine learning algorithm with potential for detecting the significance of DR. …”
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    Proceeding Paper
  10. 10

    Fault Detection and Identification in Quadrotor System (Quadrotor Robot) by Chan, Shi Jing, Pebrianti, Dwi

    Published 2016
    “…The aim of the research is to construct and design a Fault Detection and Isolation algorithm. This dynamic model is based on the first principles of the Quadrotor: Propeller model and its force as well as moments generation. …”
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    Conference or Workshop Item
  11. 11

    Reduced-rank technique for joint channel estimation in TD-SCDMA systems. by Ismail, Alyani, Sali, Aduwati, Mohd Ali, Borhanuddin, Khatun, Sabira

    Published 2013
    “…We exploit the rank deficient of H to reduce the number of parameters that characterizes this matrix. The adopted reduced rank technique is based on singular value decomposition algorithm. …”
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    Article
  12. 12

    A new model for iris data set classification based on linear support vector machine parameter's optimization by Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole

    Published 2020
    “…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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    Article
  13. 13

    Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network by Sivarao, Subramonian

    Published 2009
    “…On the other hand, when we use computers to reduce uncertainty, the computer itself can become an expert in a specific field through a variety of methods. One such method is machine learning, which involves computer algorithm to capture hidden knowledge from data. …”
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    Article
  14. 14

    Modelling of intelligent intrusion detection system: making a case for snort by Olanrewaju, Rashidah Funke, Ku zahir, Ku Nor Afiza, Asnawi, Ani Liza, Sanni, Mistura Laide, Ahmed, Abdulkadir Adekunle

    Published 2018
    “…This MLFNN with BP algorithm was simulated using MATLAB software. The performance of this classifier was evaluated based on three parameters: accuracy, sensitivity, and False Positive Rate (FPR). …”
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    Proceeding Paper
  15. 15

    Translating conventional wisdom on chicken comb color into automated monitoring of disease-infected chicken using chromaticity-based machine learning models by Bakar M.A.A.A., Ker P.J., Tang S.G.H., Baharuddin M.Z., Lee H.J., Omar A.R.

    Published 2024
    “…Logistic Regression, Support Vector Machines (SVMs), K-Nearest Neighbors (KNN), and Decision Trees have been developed to detect infected chickens using the chromaticity data. Based on the X and Z chromaticity data from the chromaticity analysis, the color of the infected chicken�s comb converged from red to green and yellow to blue. …”
    Article
  16. 16

    Hybrid vehicle engine misfire detection using Piezo-film Sensors and analysing with Z-freq / Nor Azazi Ngatiman and Mohd Zaki Nuawi by Ngatiman, Nor Azazi, Nuawi, Mohd Zaki

    Published 2018
    “…While the second phase is signal measurement using data acquisition, filtering and analysis using Z-freq method. …”
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    Article
  17. 17

    Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration by Althuwaynee, Omar F., Pradhan, Biswajeet, Ahmad, Noordin

    Published 2014
    “…This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. …”
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    Conference or Workshop Item
  18. 18

    Machine condition monitoring and fault diagnosis using spectral analysis techniques by Salami, Momoh Jimoh Eyiomika, Abdul Muthalif, Asan Gani, Pervez, T.

    Published 2001
    “…Both normal and fault signals are analyzed using the singular value decomposition (SVD) algorithm so as to compute the parameters of the auto regressive moving average (ARMA) models. …”
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    Proceeding Paper
  19. 19

    Effect of LiDAR mounting parameters and speed on HDL graph SLAM-Based 3D mapping for autonomous vehicles by Law, Jia Seng, Muhammad Aizzat, Zakaria, Younus, Maryam, Yong, Ericsson, Ismayuzri, Ishak, Mohamad Heerwan, Peeie, Muhammad Izhar, Ishak

    Published 2025
    “…This study investigates the physical calibration of a LiDAR sensor mounted on a moving vehicle and its effect on 3D map generation using the HDL Graph SLAM algorithm. HDL Graph SLAM was selected as the offline post-processing method due to its self-correcting functions for estimating and auto-correcting positional errors from LiDAR data. …”
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    Article
  20. 20

    Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor by Adilah, Abdul Ghapor

    Published 2017
    “…The simulation results indicate that the proposed method is suitable to detect a single outlier. As for the multiple outliers, a clustering algorithm is considered and a dendogram to visualise the clustering algorithm is used. …”
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    Thesis