Search Results - (( pattern detection method algorithm ) OR ( pattern selection based algorithm ))
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1
Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Recently, various techniques based on different algorithms have been developed. …”
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Swarm negative selection algorithm for electroencephalogram signals classification
Published 2009“…Such automated systems must rely on robust and effective algorithms for detection and prediction. Approach: The proposed detection system of epileptic seizure in EEG signals is based on Discrete Wavelet Transform (DWT) and Swarm Negative Selection (SNS) algorithm. …”
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Artificial immune system based on real valued negative selection algorithms for anomaly detection
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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A study on advanced statistical analysis for network anomaly detection
Published 2005“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Fault diagnostic algorithm for precut fractionation column
Published 2004“…The fault diagnostic algorithm is supported by the process history based method and developed by using Borland C++ Builder 6.0. …”
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Development Of Stereo-Matching Algorithm Based On Adaptive Weighted Prediction
Published 2019“…Comparison of this framework continue in some of the state-of-the-arts algorithm in the literature and the results is outperformed based on the proposed algorithm experimental result.…”
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A hybrid interpretable deep structure based on adaptive neuro‑fuzzy inference system, decision tree, and K‑means for intrusion detection
Published 2022“…For generating an interpretable deep architecture for identifying deep intrusion patterns, this study proposes an approach that combines ANFIS (Adaptive Network-based Fuzzy Inference System) and DT (Decision Tree) for interpreting the deep pattern of intrusion detection. …”
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Hereditary ratio of adolescent to parent based on lips analysis using canny edge detection / Nor Shamimi Kharuddin
Published 2010“…In this research, technique selection is done by doing some literature review to find the best one and also studying about the algorithm of each technique has. …”
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Pairwise clusters optimization and cluster most significant feature methods for anomaly-based network intrusion detection system (POC2MSF) / Gervais Hatungimana
Published 2018“…Anomaly-based Intrusion Detection System (IDS) uses known baseline to detect patterns which have deviated from normal behaviour. …”
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P300 detection of brain signals using a combination of wavelet transform techniques
Published 2012“…By reduction of recording EEG channels in the single trial based algorithms, the processing time of P300 detection decrease dramatically. …”
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12
Image clustering comparison of two color segmentation techniques
Published 2010“…There are many algorithm for analysing clustering each having its own method to do clustering. …”
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Traditional marble game using ant colony optimization / Muhammad Izzat Imran Che Isa
Published 2017“…The prototype is evaluated based on distance between initial position and selected marble position. …”
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14
Non-invasive pathological voice classifications using linear and non-linear classifiers
Published 2010“…In the second experiment, the detection of the specific type of voice disorders has been carried out through twoclass pattern classification problems. …”
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15
Efficient gear fault feature selection based on moth‑flame optimisation in discrete wavelet packet analysis domain
Published 2019“…Second, the MFO algorithm was utilised to select the optimal discriminative features. …”
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Feature extraction: hand shape, hand position and hand trajectory path
Published 2011“…The performance of recognition system fIrst depends on the process of getting effIcient features to represent pattern characteristics [1]. There is no algorithm which shows how to select the representation or choose the features [2] so the selection of features will depend on the application. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat
Published 2021“…Size was extracted using Extreme Point Detection algorithm and Hit or Miss Transformation method was used to extract the stroke formation pattern. …”
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Adaptive feature selection for denial of services (DoS) attack
Published 2017“…Adaptive detection is the learning ability to detect any changes in patterns in intrusion detection systems. …”
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Configuration and analysis of piezoelectric-based in socket sensory system for transfemoral prosthetic Gait detection / Farahiyah Jasni
Published 2018“…The finalized configuration that resulted in the best response was adopted and used to collect data for training and classifying the gait phase using pattern recognition method. The performance of the proposed sensory system was evaluated by checking the accuracy of the pattern recognition algorithm in detecting the gait phases at different speeds of normal walking. …”
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20
Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition
Published 2018“…Electromyography (EMG) signal is a biomedical signal which measures physical activity of human muscle.It has been acknowledged to be widely used in rehabilitation or recovery application system assisting physiotherapist to monitor a patient’s physical strength,function,motion and overall well-being by addressing the underlying physical issues.In application system associated with rehabilitation,a signal processing and classification techniques are implemented to classify EMG signal obtained.For real time application in the rehabilitation, the classification is crucial issue.The success of the signal classification depends on the selection of the features that represent a raw EMG signal in the signal processing.Therefore,a robust and resilient denoising method and spectral estimation technique have been acknowledged as necessary to distinguish and detect the EMG pattern.The present study was undertaken to determine the characteristic of EMG features using denoising method and spectral estimation technique for assessing the EMG pattern based on a supervised classification algorithm.In the study,the combination of time-frequency domain (TFD) and time domain (TD) were identified as the preferred denoising method and spectral estimation techniques.In the first part of study, the recorded EMG signal filtered the contaminated noise by using wavelet transform (WT) approach which implemented discrete wavelet transform (DWT) method of the wavelet-denoising signal. …”
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