Search Results - (( deviation detection method algorithm ) OR ( variable generation using algorithm ))

Fault detection and diagnosis using rule-based support system on fatty acid fractionation column by Yann, H. H., Ali, Mohamad Wijayanuddin, Kamsah, Mohd Zaki

“…Identification of causes, consequences and suggested actions for each deviation assisted by Hazard and Operability Study (HAZOP) analysis are generated into rule-based algorithm. …”
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Deviation detection in text using conceptual graph interchange format and error tolerance dissimilarity function by Kamaruddin, Siti Sakira, Hamdan, Abdul Razak, Abu Bakar, Azuraliza, Mat Nor, Fauzias

“…We propose a novel error tolerance dissimilarity algorithm to detect deviations in the CGIFs. We evaluate our method in the context of analyzing real world financial statements for identifying deviating performance indicators. …”
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Fault diagnostic algorithm for precut fractionation column by Heng, H. Y., Ali, Mohamad Wijayanuddin, Kamsah, Mohd. Zaki

“…Hazard and Operability Study (HAZOP) is used to support the diagnosis task. The algorithm has been successful in detecting the deviations of each variable by testing the data set. …”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

“…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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Stochastic Modelling Of Bioethanol Fermentation By Saccharomyces Cerevisiae Grown In Oil Palm Residues by Samsudin , Mohd Dinie Muhaimin

“…However, this result might differ if it is to be reduplicated due to heterogeneity of OPT sap and POME as well as variability in Baker’s yeast’s performance. Therefore, a predictability test was carried out using Monte Carlo algorithm. …”
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A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

“…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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Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor by Adilah, Abdul Ghapor

“…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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Development of a rule-based fault diagnostic advisory system for precut fractionation column by Heng, Han Yann

“…The advisory system algorithm used process history based method and presented by rule-based approach. …”
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Comparative study of clustering-based outliers detection methods in circular-circular regression model by Siti Zanariah, Satari, Nur Faraidah, Muhammad Di, Yong Zulina, Zubairi, Abdul Ghapor, Hussin

“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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Comparative study of clustering-based outliers detection methods in circular-circular regression model by Siti Zanariah Satari, Nur Faraidah Muhammad Di, Yong Zulina Zubairi, Abdul Ghapor Hussin

“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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Comparative study of clustering-based outliers detection methods in circularcircular regression model by Siti Zanariah, Satari, Nur Faraidah, Muhammad Di, Yong Zulina, Zubairi, Abdul Ghapor, Hussin

“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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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

“…In this study, we proposed multiple outliers detection in circular regression models based on the clustering algorithm. …”
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Experiment and analysis of computer vision-based wrist radial and ulnar deviation exercises by M. Zabri, Abu Bakar, Rosdiyana, Samad, Pebrianti, Dwi, Mahfuzah, Mustafa, Nor Rul Hasma, Abdullah

“…The researchers have kept on improving the existing methods by creating novel method or developing new algorithms in image processing and artificial intelligence. …”
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Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer by Iqbal Basheer, Muhammmad Yunus

“…Hence, it is critical for an anomaly detection algorithm to detect data anomalies patterns. …”
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Feature selection in intrusion detection, state of the art: A review by Rais, H.M., Mehmood, T.

“…These input features give information to the learning algorithms which used in intrusion detection system in the form of the detection method. …”
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Computer vision automation system for sorting partially overlapping tiles by Hussin, Neam Tariq

“…The CbATS consists of three main components which are a color-detection algorithm for distinguishing tiles according to the color, image segmentation that ensures the separation between partially overlapped tiles, and texture features extraction method to determine overturned tiles. …”
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Development of a computer vision-based technique for analysis of hand therapy exercise by Muhammad Zabri, Abu Bakar

“…For this purpose, the ROM exercise was developed by using the hand detection and tracking, fingertips detection, skeleton joints detection algorithms and joint angle measurement algorithm. …”
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Capacitive sensing algorithm for elderly activity detection scheme indoor environment by Arshad, Atika, Khan, Sheroz, Abdul Kadir, Kushsairy, Tasnim, Rumana

“…The detecting and tracking algorithm uses the sensory data to indicate an associated situation in order to allow elderly people with special requirements. …”
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

“…We modified the classical bootstrapping algorithm by developing a mechanism based on the robust LTS method to detect the correct number of outliers in the each bootstrap sample. …”
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The multiple outliers detection for circular univariate data using different agglomerative clustering algorithms by Nur Syahirah, Zulkipli, Siti Zanariah, Satari, Wan Nur Syahidah, Wan Yusoff

“…Then, the results performance of the agglomerative clustering algorithms were compared and the best method for certain data conditions is chosen. …”
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