Search Results - (( pattern deviation selection algorithm ) OR ( java application reoptimize algorithm ))

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  1. 1

    Fault diagnostic algorithm for precut fractionation column by Heng, H. Y., Ali, Mohamad Wijayanuddin, Kamsah, Mohd. Zaki

    Published 2004
    “…Hazard and Operability Study (HAZOP) is used to support the diagnosis task. The algorithm has been successful in detecting the deviations of each variable by testing the data set. …”
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    Conference or Workshop Item
  2. 2

    Geomorphometric analysis of landform pattern using topographic position and ASTER GDEM by Lay, Usman Salihu, Jibrin, Gambo, Tijani, Ibrahim, Pradhan, Biswajeet

    Published 2017
    “…Maximum Elevation Deviation was selected to measure the spatial landscape pattern at the maximum (3000) scale of the absolute DEV value within the scale (DEVmax), and finally, high-pass filter algorithm was used to identify the extreme topography (ridges/valleys). …”
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    Conference or Workshop Item
  3. 3

    Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control by Mohd Hanafi, Muhammad Sidik

    Published 2020
    “…This method would be a control method to activate power assist system and selected based on conditions set in the algorithm. …”
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    Thesis
  4. 4

    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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    Thesis
  5. 5

    A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

    Published 2005
    “…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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    Monograph
  6. 6

    A hybrid interpretable deep structure based on adaptive neuro‑fuzzy inference system, decision tree, and K‑means for intrusion detection by Jia, Lu, Yin Chai, Wang, Chee Siong, Teh, Xinjin, Li, Liping, Zhao, Fengrui, Wei

    Published 2022
    “…Meanwhile, for improving the efciency of training and predicting, Pearson Correlation analysis, standard deviation, and a new adaptive K-means are used to select attributes and make fuzzy interval decisions. …”
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    Article
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  10. 10

    Pairwise clusters optimization and cluster most significant feature methods for anomaly-based network intrusion detection system (POC2MSF) / Gervais Hatungimana by Hatungimana, Gervais

    Published 2018
    “…Anomaly-based Intrusion Detection System (IDS) uses known baseline to detect patterns which have deviated from normal behaviour. …”
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    Article
  11. 11

    Suspicious activities detection for anti-money laundering using machine learning techniques by Lim, Aun Chir

    Published 2025
    “…Machine learning is able to learn complex relationships within large datasets then identify anomalies that deviate from well-defined patterns. This enables machine learning model to detect those suspicious activities more accurately than traditional approaches. …”
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    Final Year Project / Dissertation / Thesis
  12. 12

    Monitoring and assessment of weld penetration condition during pulse mode laser welding using air-borne acoustic signal by Mohd Fadhlan, Mohd Yusof

    Published 2021
    “…Signal features, such as mean absolute deviation (MAD), standard deviation (SD), kurtosis (K), L-scale (LS), L-kurtosis (LK), bandpower (BP), and sum of synchrosqueezed wavelet coefficient (CSqWCsum) were extracted from the acquired sound. …”
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    Thesis
  13. 13

    UV-vis spectrophotometric and artificial neural network for estimation of ammonia in aqueous environment using cobalt(II) ions by Ling, TL, Ahmad, M, Heng, LY

    Published 2024
    “…A set of absorbance data for the [Co(NH3)(6)](2+) complex at selected wavelengths was input for ANN training using a back-propagation algorithm. …”
    Article
  14. 14

    Assessment of near-infrared and mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm plantation by Liaghat, Shohreh

    Published 2013
    “…Reflectance spectra were pre-processed and principal component analysis (PCA) was performed to obtain PC scores as input features used in different pattern recognition algorithms in order to select the best learning model of Ganoderma discrimination. …”
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    Thesis