Search Results - (( evolution classification modelling algorithm ) OR ( variable deviation detection algorithm ))
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Fault diagnostic algorithm for precut fractionation column
Published 2004“…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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Conference or Workshop Item -
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Development of a rule-based fault diagnostic advisory system for precut fractionation column
Published 2005“…Although the scheme was developed based on data of fatty acid precut fractionation column, the algorithm of fault detection and diagnosis can be extended to other chemical process by changing the x-MR chart and HAZOP for each selected monitoring variables.…”
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Thesis -
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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Thesis -
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Fault diagnostic advisory system using moving-range chart and hazard operability study.
Published 2007“…Fault is considered to occur if one variable is out of control limit. The advisory system has successfully detected and diagnosed the deviations and displayed the causes and consequences of the faults. …”
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Article -
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A study on advanced statistical analysis for network anomaly detection
Published 2005“…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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Monograph -
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Fault diagnostic advisory system using moving-range chart and hazard operability study
Published 2007“…Fault is considered to occur if one variable is out of control limit. The advisory system has successfully detected and diagnosed the deviations and displayed the causes and consequences of the faults. …”
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Article -
7
Fault detection and diagnosis using rule-based support system on fatty acid fractionation column
Published 2003“…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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Article -
8
Classification of Immunosignature Using Random Forests for Cancer Diagnosis
Published 2015“…In this work, we will develop a robust classification model that can be utilized in cancer diagnosis using immunofingerprint data. …”
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Proceeding Paper -
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Deep learning detector for pests and plant disease recognition
Published 2020“…Meanwhile, evolution in deep convolutional neural networks for image classification has rapidly improved the accuracy of object detection, classification and system recognition. …”
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Final Year Project / Dissertation / Thesis -
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Y-type Random 2-satisfiability In Discrete Hopfield Neural Network
Published 2024“…Finally, a new logic mining model namely Y-Type Random 2-Satisfiability Reverse Analysis was proposed, which showed optimal performances in terms of several metrics as compared to the existing classification models. …”
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Thesis -
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…However, the learning complexity of classification is increased due to the expansion number of learning model. …”
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Thesis -
15
Digital economy tax compliance model in Malaysia using machine learning approach
Published 2021“…The experimental results show that the ensemble method can improve the single classification model’s accuracy with the highest classification accuracy of 87.94% compared to the best single classification model. …”
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Article -
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…Feature selection was used to sort out key features for further classification. News classification into factors affecting stock market turning point was done using Naïve Bayes, Deep Learning, Generalized Linear Model (GLM) and Support Vector Machine (SVM). …”
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Book Section -
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Anomaly detection of denial-of-service network traffic attacks using autoencoders and isolation forest
Published 2026“…This paper presents an unsupervised network-based anomaly detection framework that integrates deep autoencoders with the Isolation Forest algorithm. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…Lastly, we consider the problem of detecting multiple outliers in circular regression models based on the clustering algorithm. …”
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Thesis -
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Article -
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ios Mobile Malware Deep Analysis And Classification For Social Media And Online Banking Exploitation
Published 2024thesis::master thesis