Search Results - (( java implication based algorithm ) OR ( outlier detection techniques algorithm ))

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  1. 1
    Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor

    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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  2. 2
    The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model

    The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model by Nur Faraidah, Muhammad Di, Siti Zanariah, Satari

    Published 2017
    “…In this study, we proposed multiple outliers detection in circular regression models based on the clustering algorithm. …”
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  3. 3
    Outlier Detection Technique in Data Mining: A Research Perspective

    Outlier Detection Technique in Data Mining: A Research Perspective by Mansur, M. O., Md. Sap, Mohd. Noor

    Published 2005
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  4. 4
    Machine Learning Approaches to Advanced Outlier Detection in Psychological Datasets

    Machine Learning Approaches to Advanced Outlier Detection in Psychological Datasets by Abri K.Al., Sidhu M.S.

    Published 2025
    “…In conclusion, while individual algorithms provide distinct perspectives, ensemble techniques enhance the accuracy and consistency of outlier detection. …”
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  5. 5
    Single-linkage method to detect multiple outliers with different outlier scenarios in circular regression model

    Single-linkage method to detect multiple outliers with different outlier scenarios in circular regression model by Siti Zanariah, Satari, Nur Faraidah, Muhammad Di, Roslinazairimah, Zakaria

    Published 2018
    “…Single-linkage is one of the algorithms in agglomerative clustering technique that can be used to detect outliers. …”
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  6. 6
    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares

    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

    Published 2009
    “…To rectify this problem, we propose a Dynamic Robust Bootstrap-LTS based (DRBLTS) algorithm where the percentage of outliers in each bootstrap sample is detected. …”
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  7. 7
    Automatic filtering of far outliers in multibeam echo sounding dataset using robust detection algorithms

    Automatic filtering of far outliers in multibeam echo sounding dataset using robust detection algorithms by Mahmud, Mohd. Razali, Mohd. Yusof, Othman

    Published 2005
    “…This paper elaborates the techniques used for the detection and elimination of the far outliers in the MBES dataset, known as robust detection algorithms. …”
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  8. 8
    An Evolutionary Stream Clustering Technique for Outlier Detection

    An Evolutionary Stream Clustering Technique for Outlier Detection by Supardi, N.A., Abdulkadir, S.J., Aziz, N.

    Published 2020
    “…Later, this algorithm will be extended to optimize the model in detecting outlier on data streams. …”
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  9. 9
    A systematic literature review on outlier detection in wireless sensor networks

    A systematic literature review on outlier detection in wireless sensor networks by Safaei, Mahmood, Asadi, Shahla, Driss, Maha, Boulila, Wadii, Alsaeedi, Abdullah, Chizari, Hassan, Abdullah, Rusli, Safaei, Mitra

    Published 2020
    “…The current paper presents an improved taxonomy of outlier detection techniques. This will help researchers and practitioners to find the most relevant and recent studies related to outlier detection in WSNs. …”
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  10. 10
    Modified sequential fences for identifying univariate outliers

    Modified sequential fences for identifying univariate outliers by Wong, Hui Shein

    Published 2016
    “…The modified sequential fences method is found can accurately detect the outliers in positively skewed distribution. …”
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  11. 11
    Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques

    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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  12. 12
    A Review of Unsupervised Machine Learning Frameworks for Anomaly Detection in Industrial Applications

    A Review of Unsupervised Machine Learning Frameworks for Anomaly Detection in Industrial Applications by Usmani, U.A., Happonen, A., Watada, J.

    Published 2022
    “…Currently, academic literature does not really cover the topic of unsupervised machine learning techniques for anomaly detection. This paper provides an overview of the current deep learning and unsupervised machine learning techniques for anomaly detection and discusses the fundamental challenges in anomaly detection. …”
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  13. 13
    Detection Of Outliers And Structural Breaks In Structural Time Series Model Using Indicator Saturation Approach

    Detection Of Outliers And Structural Breaks In Structural Time Series Model Using Indicator Saturation Approach by Rose, Farid Zamani Che

    Published 2023
    “…The proposed technique is capable to detect the location, duration, magnitude and number of structural changes in time series data. …”
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  14. 14
    Dynamic intrusion detection method for mobile ad hoc network using CPDOD algorithm

    Dynamic intrusion detection method for mobile ad hoc network using CPDOD algorithm by Abdel-Fatah, Farhan, Md Dahalin, Zulkhairi, Jusoh, Shaidah

    Published 2010
    “…In this paper, we propose a novel intrusion detection method by combining two anomaly methods Conformal Predictor k-nearest neighbor and Distancebased Outlier Detection (CPDOD) algorithm. …”
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  15. 15
    A Machine Learning Classification Approach To Detect Tls-Based Malware Using Entropy-Based Flow Set Features

    A Machine Learning Classification Approach To Detect Tls-Based Malware Using Entropy-Based Flow Set Features by Keshkeh, Kinan

    Published 2022
    “…This study also investigates TLSMalDetect detection performance using seven ML classification algorithms and identifies the one with the highest accuracy.…”
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  16. 16
    A Machine Learning Classification Approach to Detect TLS-based Malware using Entropy-based Flow Set Features

    A Machine Learning Classification Approach to Detect TLS-based Malware using Entropy-based Flow Set Features by Keshkeh, Kinan, Jantan, Aman, Alieyan, Kamal

    Published 2022
    “…Due to the complexity of TLS traffic decryption, several anomaly-based detection studies have been conducted to detect TLS-based malware using different features and machine learning (ML) algorithms. …”
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  17. 17
    Electricity Anomaly Point Detection using Unsupervised Technique Based on Electricity Load Prediction Derived from Long Short-Term Memory

    Electricity Anomaly Point Detection using Unsupervised Technique Based on Electricity Load Prediction Derived from Long Short-Term Memory by Salleh N.S.M., Saripuddin M., Suliman A., Jorgensen B.N.

    Published 2023
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  18. 18
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…At the same time, it provides a clear insight into the techniques developed for anomaly detection problems. …”
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  19. 19
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    “…At the same time, it provides a clear insight into the techniques developed for anomaly detection problems. …”
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  20. 20
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…At the same time, it provides a clear insight into the techniques developed for anomaly detection problems. …”
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