Search Results - (( variable detection method algorithm ) OR ( _ normalization 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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2
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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3
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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4
Artificial immune system based on real valued negative selection algorithms for anomaly detection
Published 2015“…With respect to all the algorithms, V-Detector proved to be superior and surpassed all other algorithms based on performance and execution time.…”
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5
Image Based Congestion Detection Algorithms And Its Real Time Implementation
Published 2015“…The proposed system uses a fast and reliable method to detect traffic congestions. The methodology includes vehicle detection by using backlight pairing feature algorithm and modified Watershed algorithm. …”
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6
Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC)
Published 2006“…The present fault detection and diagnosis (FDD) method based on MSPC uses statistical control charts and contribution plots. …”
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7
Fault detection and diagnosis using correlation coefficients
Published 2005“…This research is to formulate a FDD algorithm based on MSPC via correlation coefficients. …”
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8
Robust remote heart rate estimation from multiple asynchronous noisy channels using autoregressive model with Kalman filter
Published 2019“…The results of three experiments demonstrate that our algorithm substantially outperforms all previous methods. …”
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Heartbeat Anomaly Detection Method Based on Electrocardiogram using Improved Certainty Cognitive Map
Published 2023“…This research has 3 objectives To develop algorithms for detecting heart conditions as either abnormal or normal using the modified cognitive map (CM) approach, To develop detection algorithms for anomalous heart conditions based on the enhancement of Certainty Factor (CF) technique, and To evaluate and validate the effectiveness of the new proposed model specifically the Certainty Cognitive Map (CCM) for identifying heart defects. …”
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10
An integrated anomaly intrusion detection scheme using statistical, hybridized classifiers and signature approach
Published 2015“…Detection methods based on statistical and data mining techniques are widely deployed as anomaly-based detection system (ADS). …”
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11
Fault detection and diagnosis using rule-based support system on fatty acid fractionation column
Published 2003“…Process history based methods (rule-based feature extraction) is used to implement the FDD rule-based support system. …”
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12
Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm
Published 2015“…We then review the state-of-the-art US-based CAD techniques that utilize a range of image texture based features like entropy, Local Binary Pattern (LBP), Haralick textures and run length matrix in several automated decision making algorithms. …”
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13
Investigation of fault detection and isolation accuracy of different Machine learning techniques with different data processing methods for gas turbine
Published 2022“…The faulty and non-faulty data were balanced, smoothed, corrected and normalized. Finally, the classification accuracy of the machine learning techniques was analyzed. …”
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Investigation of fault detection and isolation accuracy of different Machine learning techniques with different data processing methods for gas turbine
Published 2022“…The faulty and non-faulty data were balanced, smoothed, corrected and normalized. Finally, the classification accuracy of the machine learning techniques was analyzed. …”
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15
Robust Kernel Density Function Estimation
Published 2010“…The accuracy of the proposed new method was compared with the location and scale estimators based on M. …”
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16
Computer-aided diagnosis of diabetic subjects by heart rate variability signals using discrete wavelet transform method
Published 2015“…These features are ranked by using various ranking methods, namely, Bhattacharyya space algorithm, t-test, Wilcoxon test, Receiver Operating Curve (ROC) and entropy. …”
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Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…The results obtained from the simulation study and real data sets indicate that the proposed method possesses high detection power with minimal misclassification error compared to the MRCD and MDP methods. …”
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18
Comparing seabed roughness result from QPS fledermaus software, benthic trrain modeler [BTM] and developed model derived FRM slope variability algorithm for hard coral reef detecti...
Published 2018“…In this study, several models has been created which are from QPS Fledermaus model, BTM model and Slope Variability model. Slope variability model is an algorithm that is being used for detecting terrain roughness. …”
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19
A real time road marking detection system on large variability road images database
Published 2017“…One of the first embedded system is a lane detection system, which was implemented using road marking detection algorithms with the aim to produce a system that is able to detect various shapes of road markings on the images that are captured under various imaging conditions. …”
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20
Coronary artery stenosis detection and visualization / Tang Sze Ling
Published 2015“…In contrast to the conventional methods which perform detection from a single image, the stenosis detection algorithm using two images from various view angles to avoid false positive (stenosis overestimated) and false negative (stenosis underestimated). …”
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