Search Results - data distribution ((factor algorithm) OR (detection algorithm))

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  1. 1

    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

    Published 2025
    “…The hybrid algorithm was implemented to minimise the length of time needed to address the massive scale of the detected parallel power load abnormalities. …”
    Article
  2. 2

    Design and analysis of management platform based on financial big data by Chen, Yuhua, Mustafa, Hasri, Zhang, Xuandong, Liu, Jing

    Published 2023
    “…In order to make financial big data generate business value and improve the information application level of financial management, aiming at the high error rate of current financial data classification system, this article adopts the fuzzy clustering algorithm to classify financial data automatically, and adopts the local outlier factor algorithm with neighborhood relation (NLOF) to detect abnormal data. …”
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    Article
  3. 3
  4. 4

    Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques by Farhan, Farhan Abdel-Fattah Ahmad

    Published 2011
    “…The transductive conformal prediction and outlier detection have been employed for feature selection algorithm. …”
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    Thesis
  5. 5

    ETERS: A comprehensive energy aware trust-based efficient routing scheme for adversarial WSNs by Khan, T., Singh, K., Hasan, M.H., Ahmad, K., Reddy, G.T., Mohan, S., Ahmadian, A.

    Published 2021
    “…However, a trust-based attack detection algorithm (TADA) assesses the reliability of SNs to detect internal attacks. …”
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    Article
  6. 6

    Energy and performance efficient resource allocation for cloud-based data centers by Akhter, Nasrin

    Published 2015
    “…In this study, we found that our proposed algorithms able to reduce energy consumption by 3% and 19% for host overload detection and VM selection algorithm respectively.…”
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    Thesis
  7. 7

    Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation by Chen, Qipeng, Xiong, Qiaoqiao, Huang, Haisong, Tang, Saihong, Liu, Zhenghong

    Published 2024
    “…In response to the current issues of poor real-time performance, high computational costs, and excessive memory usage of object detection algorithms based on deep convolutional neural networks in embedded devices, a method for improving deep convolutional neural networks based on model compression and knowledge distillation is proposed. …”
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    Article
  8. 8

    Embedded vision system development using 32-bit Single Board Computer and GNU/Linux by Nur Farhan, Kahar

    Published 2011
    “…The overall software design is divided into three modules which are Image Acquisition, Image Processing and Object Detection, and Data Transmission module. The image processing algorithm includes color space conversion and motion analysis technique. …”
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    Thesis
  9. 9

    Distributed Online Averaged One Dependence Estimator (DOAODE) Algorithm for Multi-class Classification of Network Anomaly Detection System by R.Badlishah, Ahmad, Nawir, M., Amir, A, Yaakob, N, Mat Safar, A, Mohd Warip, M.N, Zunaidi, I

    Published 2019
    “…Therefore, this paper aims to develop an effective and efficient network anomaly detection system by using distributed online averaged one dependence estimator (DOAODE) classification algorithm for multi-class network data to overcome these issues. …”
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    Conference or Workshop Item
  10. 10

    Distributed Online Averaged One Dependence Estimator (DOAODE) Algorithm for Multi-class Classification of Network Anomaly Detection System by Badlishah, Ahmad, Nawir, M., Amir, A, Yaakob, N, Mat Safar, A, Mohd Warip, M.N, Zunaidi, I

    Published 2019
    “…Therefore, this paper aims to develop an effective and efficient network anomaly detection system by using distributed online averaged one dependence estimator (DOAODE) classification algorithm for multi-class network data to overcome these issues. …”
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    Conference or Workshop Item
  11. 11

    Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer by Iqbal Basheer, Muhammmad Yunus

    Published 2023
    “…Hence, it is critical for an anomaly detection algorithm to detect data anomalies patterns. …”
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    Thesis
  12. 12

    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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    Article
  13. 13

    Broken Conductor Detection on Power Distribution Feeder by Sulaiman , Marizan, Tawafan, Adnan, Ibrahim, Zulkifilie

    Published 2013
    “…It proposes an intelligent algorithm using the Fuzzy Subtractive Clustering Model (FSCM) to detect the high impedance fault. …”
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    Article
  14. 14

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

    Published 2004
    “…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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    Thesis
  15. 15

    Detecting High Impedance Fault in Power Distribution Feeder with Fuzzy Subtractive Clustering Model by Sulaiman , Marizan, Adnan, Tawafan, Ibrahim, Zulkifilie

    Published 2013
    “…This paper presents the algorithm for HIF detection based on the amplitude of third and fifth harmonics of current, voltage and power. …”
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    Article
  16. 16

    An eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in khyber-pakhtunkhwa, Pakistan by Ullah, S., Daud, H., Dass, S.C., Hadi, F.-T., Khalil, A.

    Published 2018
    “…Identifying the abnormally high-risk regions in a spatiotemporal space that contains an unexpected disease count is helpful to conduct surveillance and implement control strategies. The EigenSpot algorithm has been recently proposed for detecting space-time disease clusters of arbitrary shapes with no restriction on the distribution and quality of the data, and has shown some promising advantages over the state-of-the-art methods. …”
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    Article
  17. 17

    An eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in khyber-pakhtunkhwa, Pakistan by Ullah, S., Daud, H., Dass, S.C., Hadi, F.-T., Khalil, A.

    Published 2018
    “…Identifying the abnormally high-risk regions in a spatiotemporal space that contains an unexpected disease count is helpful to conduct surveillance and implement control strategies. The EigenSpot algorithm has been recently proposed for detecting space-time disease clusters of arbitrary shapes with no restriction on the distribution and quality of the data, and has shown some promising advantages over the state-of-the-art methods. …”
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    Article
  18. 18

    Detection of leak size and its location in a water distribution system by using K-NN / Nasereddin Ibrahim Sherksi by Sherksi, Nasereddin Ibrahim

    Published 2020
    “…The system is simulated using EPANET (Environmental Prediction Agency Network) software based on actual water distribution system (WDS) data from Benghazi city, Libya. …”
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    Thesis
  19. 19

    Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

    Published 2019
    “…One of the challenging issues for a grid-connected distributed generation is to find a suitable technique to detect an islanding problem. …”
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    Thesis
  20. 20

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

    Published 2005
    “…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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    Monograph