Search Results - (( data evaluation method algorithm ) OR ( data detection method algorithm ))

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  1. 1
    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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  2. 2
    Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction

    Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction by Alkawsi G., Al-amri R., Baashar Y., Ghorashi S., Alabdulkreem E., Kiong Tiong S.

    Published 2024
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  3. 3
    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak

    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

    Published 2019
    “…However, in many cases it is not possible to get such large amounts of data due to certain constraints. Therefore, there is a need to find a new valuation method that does not require large data sets yet yields the same results. …”
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  4. 4
    Experimental evaluation of data fusion algorithm for residual generation in detecting UAV servo actuator fault

    Experimental evaluation of data fusion algorithm for residual generation in detecting UAV servo actuator fault by Sahwee Z., Rahman N.A., Sahari K.S.M.

    Published 2023
    “…Algorithms; Data fusion; Hardware; Military vehicles; Redundancy; Software reliability; Unmanned aerial vehicles (UAV); Analytical redundancy; Data fusion algorithm; Experimental evaluation; Fault detection algorithm; Hostile environments; Model reference methods; On-board fault detection; Software and hardwares; Fault detection…”
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  5. 5
    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
    “…Hence, it is critical for an anomaly detection algorithm to detect data anomalies patterns. …”
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  6. 6
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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  7. 7
    Detection of multiple outliners in linear regression using nonparametric methods

    Detection of multiple outliners in linear regression using nonparametric methods by Adnan, Robiah

    Published 2004
    “…The predicted and residual values are obtained from an ordinary least squares fit of the data. The algorithm is described and is shown to perform well on classic multiple outlier data sets. …”
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  8. 8
    Assessment of CDA and Morphlink-C Algorithms method in crack detection using [Multirotor DJ1 phantom 3] image / Muhammad Hafizi Abd Rahaim

    Assessment of CDA and Morphlink-C Algorithms method in crack detection using [Multirotor DJ1 phantom 3] image / Muhammad Hafizi Abd Rahaim by Abd Rahaim, Muhammad Hafizi

    Published 2018
    “…Then, the image was being processed in the photogrammetry software to produce the orthomosaic and point cloud data. These data model then was evaluated their availability of processed image to detect crack using CDA and MorphLink-C algorithms. …”
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  9. 9
    Evaluating integrated weight linear method to class imbalanced learning in video data

    Evaluating integrated weight linear method to class imbalanced learning in video data by Mohd Apandi, Ziti Fariha, Mustapha, Norwati, Affendey, Lilly Suriani

    Published 2011
    “…This paper proposed an Integrated Weight Linear (IWL) method that integrate weight linear algorithm (WL) with principle component analysis (PCA) to eliminate imbalanced dataset in soccer video data. …”
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  10. 10
    Temporal video segmentation using squared form of Krawtchouk-Tchebichef moments

    Temporal video segmentation using squared form of Krawtchouk-Tchebichef moments by Abdulhussain, Sadiq H.

    Published 2018
    “…TVS algorithm design is still challenging because most of the recent methods are unable to achieve robust detection for different types of transitions: hard transition (HT) and soft transition (ST). …”
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  11. 11
    Failure detection analysis of grid-connected photovoltaic system using an improved comparative based method / Fatin Azirah Mohd Shukor

    Failure detection analysis of grid-connected photovoltaic system using an improved comparative based method / Fatin Azirah Mohd Shukor by Mohd Shukor, Fatin Azirah

    Published 2022
    “…Moreover, the evaluation on the reliability of the FD analysis algorithm applied using large amount of field data instead of simulated data is still limited and significant, especially in the context of tropical climate conditions. …”
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  12. 12
    Missing Value Imputation for PM10 Concentration in Sabah using Nearest Neighbour Method(NNM) and Expectation-Maximization (EM) Algorithm

    Missing Value Imputation for PM10 Concentration in Sabah using Nearest Neighbour Method(NNM) and Expectation-Maximization (EM) Algorithm by Muhammad Izzuddin Rumaling, Chee, Fuei Pien, Jedol Dayou, Chang, Jackson Hian Wui, Steven Soon Kai Kong, Justin Sentian

    Published 2020
    “…To fill in missing data, Nearest Neighbour Method(NNM) and Expectation Maximization(EM) algorithm are the two most widely used methods. …”
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  13. 13
    Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods

    Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods by Mohd Sharif, Zakaria, Mohammad Fadhil, Abas, Fatimah, Dg Jamil, Norhafidzah, Mohd Saad, Addie, Irawan, Pebrianti, Dwi

    Published 2024
    “…The fitness function with the Genetic Algorithm (GA) optimization method is tested and evaluated based on Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and detection time. 51 sets of data have been collected using software in the loop (SITL) methods and are used to determine the effectiveness of the proposed fitness function and GA. …”
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  14. 14
    An ensemble feature selection method to detect web spam

    An ensemble feature selection method to detect web spam by Oskouei, Mahdieh Danandeh, Razavi, Seyed Naser

    Published 2018
    “…Web spam detection is one of research fields of data mining. …”
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  15. 15
    Blotch removal using multi-level scanning, shape analysis, and meta heuristic techniques

    Blotch removal using multi-level scanning, shape analysis, and meta heuristic techniques by Khammar, Mohammad Reza

    Published 2015
    “…The algorithms were applied to two real image sequences which were contaminated to unknown blotches and the results were extracted for evaluation of proposed methods. …”
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  16. 16
    On density-based data streams clustering algorithms: A survey

    On density-based data streams clustering algorithms: A survey by Teh, Y.W.

    Published 2017
    “…Recently, a lot of density-based clustering algorithms are extended for data streams. The main idea in these algorithms is using density-based methods in the clustering process and at the same time overcoming the constraints, which are put out by data stream’s nature. …”
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  17. 17
    An eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in khyber-pakhtunkhwa, Pakistan

    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
    “…We evaluated the proposed method using the monthly data on measles cases in Khyber-Pakhtunkhwa, Pakistan (Jan 2016- Dec 2016), and the efficiency was compared with the state-of-the-art methods: EigenSpot and Space-time scan statistic (SaTScan). …”
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  18. 18
    An eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in khyber-pakhtunkhwa, Pakistan

    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
    “…We evaluated the proposed method using the monthly data on measles cases in Khyber-Pakhtunkhwa, Pakistan (Jan 2016- Dec 2016), and the efficiency was compared with the state-of-the-art methods: EigenSpot and Space-time scan statistic (SaTScan). …”
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  19. 19
    Test case generation from state machine with OCL constraints using search-based techniques / Aneesa Ali Ali Saeed

    Test case generation from state machine with OCL constraints using search-based techniques / Aneesa Ali Ali Saeed by Aneesa Ali, Ali Saeed

    Published 2017
    “…Generating test cases from Unified Modeling Language (UML) state machine models has two major challenges: generating feasible paths, and generating data to satisfy the paths. The existing infeasible path detection methods are restricted to extended finite state machine (EFSM) models with integer data type only. …”
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  20. 20
    Evaluation of the Transfer Learning Models in Wafer Defects Classification

    Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

    Published 2022
    “…Each image went through the embedding process by the evaluated algorithms. This enhanced image data numbers then went through Logistic Regression as a classifier. …”
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