Search Results - (( data detection based algorithm ) OR ( program implementation mining algorithm ))

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  1. 1
    Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining

    Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining by Ang, Yuhao, Mohd Shafri, Helmi Zulhaidi, Al-Habshi, Mohammed Mustafa

    Published 2025
    “…No previous study has investigated Orange mining tool as visual programming approach in analysing hyperspectral reflectance data, especially in crop disease detection. …”
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  2. 2
    Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak

    Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak by Ishak, Najihah Salsabila

    Published 2021
    “…Machine learning is an implementation of artificial intelligence (Al) that allows systems to learn and build on knowledge without being directly programmed automatically. …”
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  3. 3
    Data mining techniques for transformer failure prediction model: A systematic literature review

    Data mining techniques for transformer failure prediction model: A systematic literature review by Ravi N.N., Mohd Drus S., Krishnan P.S.

    Published 2023
    Conference Paper
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  4. 4
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…Finding a good classification algorithm is an important component of many data mining projects. …”
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  5. 5
    Enhancing predictive crime mapping model using association rule mining for geographical and demographic structure

    Enhancing predictive crime mapping model using association rule mining for geographical and demographic structure by Asmai, S. A.

    Published 2014
    “…The other 40% of the dataset is used to test generated rules. A simple program of C++ is implemented using Microsoft Visual Studio to test generated rules until accuracy of performance is obtained. …”
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  6. 6
    Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer

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

    Published 2023
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  7. 7
    Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif

    Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

    Published 2014
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  8. 8
    Artificial immune system based on real valued negative selection algorithms for anomaly detection

    Artificial immune system based on real valued negative selection algorithms for anomaly detection by Khairi, Rihab Salah

    Published 2015
    “…This shows that the Negative Selection Algorithms are equipped with the capabilities of detecting changes in data, thus appropriate for anomaly detection. …”
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  9. 9
    Algorithm enhancement for host-based intrusion detection system using discriminant analysis

    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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  10. 10
    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network

    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

    Published 2016
    “…In this research, a hand-written character recognition model are implemented in C++ programming with ability to classify digits 0, 1, 2, and 3. …”
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  11. 11
    Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream

    Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream by Abdulateef, Alaa Fareed

    Published 2023
    “…Existing clustering algorithms for outlier detection encounter significant challenges due to insufficient data pre-processing methods and the absence of a suitable data summarization framework for effective data stream clustering. …”
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  12. 12
    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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  13. 13
    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi

    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

    Published 2019
    “…Despite attempts to solve the data clustering issues, there are also many variants of modified algorithms in traditional information clustering that attempt to solve issues such as clustering algorithms based on condensation. …”
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  14. 14
    Detecting Duplicate Entry in Email Field using Alliance Rules-based Algorithm

    Detecting Duplicate Entry in Email Field using Alliance Rules-based Algorithm by Arif, Hanafi, Sulaiman, Harun, Enggari, Sofika, Rani, Larissa Navia

    Published 2016
    “…It provides an algorithm to the discovery of error and duplicates entries in the data sets of existing data warehouse. …”
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  15. 15
    MotionSure: a cloud-based algorithm for detection of injected object in data in motion

    MotionSure: a cloud-based algorithm for detection of injected object in data in motion by Islam, Thouhedul, Olanrewaju, Rashidah Funke, Khalifa, Othman Omran

    Published 2017
    “…Although there are few algorithms for data protection in the Cloud, However, such algorithms are still prone to attack, especially in real-time data movement due to the mechanism employed. …”
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  16. 16
    Integrating genetic algorithms and fuzzy c-means for anomaly detection

    Integrating genetic algorithms and fuzzy c-means for anomaly detection by Chimphlee, Witcha, Abdullah, Abdul Hanan, Sap, Noor Md., Chimphlee, Siriporn, Srinoy, Surat

    Published 2005
    “…Clustering-based intrusion detection algorithm which trains on unlabeled data in order to detect new intrusions. …”
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  17. 17
    Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system

    Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system by Maseer, Ziadoon Kamil

    Published 2022
    “…However, the current DBN.NIDS model is still ineffective for large-scale real-world data due to some issues: 1) the pre-training of the DBN algorithm includes simple feature learning which does not work very well to extract important features from the attack data, 2) the classification task of the DBN algorithm is a poor detection for imbalanced class dataset and 3) the design of the DBN model could be weak and need to be continuously updated by modern definitions of abnormal to detect recent attacks. …”
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  18. 18
    The effect of different similarity distance measures in detecting outliers using single-linkage clustering algorithm for univariate circular biological data

    The effect of different similarity distance measures in detecting outliers using single-linkage clustering algorithm for univariate circular biological data by Nur Syahirah, Zulkipli, Siti Zanariah, Satari, Wan Nur Syahidah, Wan Yusoff

    “…Clustering algorithms can be used to create an outlier detection procedure in univariate circular data. …”
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  19. 19
    Missing tags detection algorithm for radio frequency identification (RFID) data stream

    Missing tags detection algorithm for radio frequency identification (RFID) data stream by Zainudin, Nur 'Aifaa

    Published 2019
    “…Thus in this research, an AC complement algorithm with hashing algorithm and Detect False Negative Read algorithm (DFR) is used to developed the Missing Tags Detection Algorithm (MTDA). …”
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  20. 20
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

    Published 2022
    “…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. …”
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