Search Results - (( model detection method algorithm ) OR ( event detection system algorithm ))*

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  1. 1
    Methods of intrusion detection in information security incident detection: a comparative study

    Methods of intrusion detection in information security incident detection: a comparative study by Tan, Fui Bee, Yau, Ti Dun, M. N. M., Kahar

    Published 2018
    “…These algorithms and methods provide fast and high rate of detection. …”
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  2. 2
    Improved abnormal detection using self-adaptive social force model for visual surveillance

    Improved abnormal detection using self-adaptive social force model for visual surveillance by Wan Nur Azhani, W. Samsudin

    Published 2017
    “…The abnormal detection in a crowd is a noteworthy research topic in automated surveillance system in public places. …”
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  3. 3
    Improving robotic grasping system using deep learning approach

    Improving robotic grasping system using deep learning approach by Mohannad K. H., Farag

    Published 2020
    “…This research aimed to develop a Deep Learning grasp detection model and a slip detection algorithm and integrating them into one innovative robotic grasping system. …”
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  4. 4
    REAL TIME ABNORMAL SOUND DETECTION AND CLASSIFICATION FOR HOME ENVIRONMENT

    REAL TIME ABNORMAL SOUND DETECTION AND CLASSIFICATION FOR HOME ENVIRONMENT by MOHAMED AMIN, SITI NUR AZIMAH

    Published 2011
    “…There are various algorithms available to identify and classify the abnormal event sound. …”
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  5. 5
    A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network

    A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network by Mohammad Azmi Ridwan, Dr.

    Published 2023
    “…This thesis proposes a hybrid ML-based intrusion detection system (ML-IDS) and ML-based intelligent routing algorithm (ML-RA) for MPLS network. …”
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  6. 6
    A detailed description on unsupervised heterogeneous anomaly based intrusion detection framework

    A detailed description on unsupervised heterogeneous anomaly based intrusion detection framework by Udzir, Nur Izura, Hajamydeen, Asif Iqbal

    Published 2019
    “…Observing network traffic flow for anomalies is a common method in Intrusion Detection. More effort has been taken in utilizing the data mining and machine learning algorithms to construct anomaly based intrusion detection systems, but the dependency on the learned models that were built based on earlier network behaviour still exists, which restricts those methods in detecting new or unknown intrusions. …”
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  7. 7
    Power quality problem classification based on Wavelet Transform and a Rule-Based method

    Power quality problem classification based on Wavelet Transform and a Rule-Based method by Nallagownden, Perumal

    Published 2010
    “…This paper describes a Wavelet Transform and Rule-Based method for detection and classification of various events of power quality disturbances. …”
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  8. 8
    A computational model of a norm's yield

    A computational model of a norm's yield by Itaiwi A.-M.K., Ahmad M.S., Tang A.Y.C., Mahmoud M.A.

    Published 2023
    “…Computation theory; Computational methods; Robotics; Computational model; Mining algorithms; norm benefits; norm yield; Normative agents; Norms detections; Reasoning ability; Multi agent systems…”
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  9. 9
    Detecting Arcing Faults in Switchgear by Using Deep Learning Techniques

    Detecting Arcing Faults in Switchgear by Using Deep Learning Techniques by Mohammed Alsumaidaee Y.A., Yaw C.T., Koh S.P., Tiong S.K., Chen C.P., Tan C.H., Ali K., Balasubramaniam Y.A.L.

    Published 2024
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  10. 10
    Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method

    Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method by Chuah , Heng keow, Nallagownden, Perumal, Kondapalli, K.S. Rama Rao

    Published 2010
    “…This paper describes a Wavelet Transform and Rule-Based method for detection and classification of various events of power quality disturbances. …”
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  11. 11
    Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method

    Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method by keow, Chuah Heng, Nallagownden, Perumal, K. S. , Rama Rao

    Published 2010
    “…This paper describes a Wavelet Transform and Rule-Based method for detection and classification of various events of power quality disturbances. …”
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  12. 12
    Islanding detection in grid-connected photovoltaic distributed generation using inverter DC-Link voltage

    Islanding detection in grid-connected photovoltaic distributed generation using inverter DC-Link voltage by Kumo, Mohammed Saidu

    Published 2017
    “…The most significant shortcoming of passive islanding detection methods is the presence of large non-detection zone (NDZ), which is a region of power mismatch between the DG and the local load where islanding cannot be timely detected. …”
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  13. 13
    POWER QUALITY CLASSIFICATION WITH DE-NOISING SCHEME USING WAVELET TRANSFORM AND RULE- BASED METHOD

    POWER QUALITY CLASSIFICATION WITH DE-NOISING SCHEME USING WAVELET TRANSFORM AND RULE- BASED METHOD by HENG KEOW, CHUAH

    Published 2012
    “…Thus it is a suitable model to be used in real time implementation through a Digital Signal Processor (DSP)- based embedded system for power quality disturbances detection and classification.…”
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  14. 14
    Fault Tolerance For Two Wheel Mobile Robot Using FSM (Finite State Machine)

    Fault Tolerance For Two Wheel Mobile Robot Using FSM (Finite State Machine) by Chan, Shi Jing, Pebrianti, Dwi, M. F., Abas, Bayuaji, Luhur

    Published 2017
    “…Fault Tolerance (FT) enables system to continue operating despite in the event of failures. …”
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  15. 15
    Development of river water level estimation from surveillance cameras for flood monitoring system using deep learning techniques

    Development of river water level estimation from surveillance cameras for flood monitoring system using deep learning techniques by Muhadi, Nur 'Atirah

    Published 2022
    “…The findings demonstrated that these methods are handcrafted and the algorithms need to be changed when applying to different images, which is not practical to be used during flood disasters. …”
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  16. 16
    Arima model time-series forecasting for structural monitoring using RTK-GPS

    Arima model time-series forecasting for structural monitoring using RTK-GPS by Anshah, Siti Aminah, Ahmad, Anuar, Mat Amin, Zulkarnaini

    Published 2008
    “…In this paper, a time series algorithm is presented for damage identification and forecasting to detect any movement of the structure. …”
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  17. 17
    Real time power quality event detection using continuous wavelet transform

    Real time power quality event detection using continuous wavelet transform by Tan R.H.G., Ramachandaramurthy V.K.

    Published 2023
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  18. 18
    Adaptive Neural Subtractive Clustering Fuzzy Inference System for the Detection of High Impedance Fault on Distribution Power System

    Adaptive Neural Subtractive Clustering Fuzzy Inference System for the Detection of High Impedance Fault on Distribution Power System by Tawafan, Adnan, Sulaiman , Marizan, Ibrahim, Zulkifilie

    Published 2012
    “…The results show that the proposed algorithm can distinguish successfully HIFs from other events in distribution power system…”
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  19. 19
    High Impedance Fault Detection on Power Distribution Feeder

    High Impedance Fault Detection on Power Distribution Feeder by Sulaiman , Marizan, Tawafan, Adnan, Ibrahim, Zulkifilie

    Published 2012
    “…The results show that the proposed algorithm can distinguish successfully HIFs from other events in distribution power system.…”
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  20. 20
    Test Data Generation for Event Driven System Using Bees Algorithm

    Test Data Generation for Event Driven System Using Bees Algorithm by Mohammed Zabil, Mohd H., Kamal Z., Zamli

    Published 2013
    “…For an event driven system, the order of the event sequence should also be tested to detect failure in any possible sequences of the event. …”
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