Search Results - (( data implication mining algorithm ) OR ( variable detection based algorithm ))
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1
Intelligent mining of large-scale bio-data: bioinformatics applications
Published 2017“…It also highlights some future perspectives of data mining in bioinformatics that can inspire further developments of data mining instruments. …”
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Observer-based fault detection with fuzzy variable gains and its application to industrial servo system
Published 2020“…The proposed fault detection algorithm employs a fuzzy logic-based approach with the objective of finding the appropriate observer gains that could cope with the different working conditions. …”
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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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Thesis -
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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 proposed algorithm has been applied to detect outliers in the high dimensional data. …”
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5
Minimization of Test Cases and Fault Detection Effectiveness Improvement through Modified Reduction with Selective Redundancy Algorithm
Published 2007“…Then the algorithm gathers all the test cases based on the definition occurrence and def-use pair if they cover same definition occurrence of one variable but they don’t cover def-use pair of the same variable. …”
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Evaluation and optimization of frequent, closed and maximal association rule based classification
Published 2014“…Real world applications of association rule mining have well-known problems of discovering a large number of rules, many of which are not interesting or useful for the application at hand.The algorithms for closed and maximal item sets mining significantly reduce the volume of rules discovered and complexity associated with the task, but the implications of their use and important differences with respect to the generalization power, precision and recall when used in the classification problem have not been examined.In this paper, we present a systematic evaluation of the association rules discovered from frequent, closed and maximal item set mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriate sequence of usage.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data/items, and detailed evaluation of rule sets is provided as a whole and w.r.t individual classes. …”
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Organizational Culture Automated Audit System (OCAAS)
Published 2017“…Several state of the art technologies and techniques were used to design and developed OCAAS which include the use of machine learning and sentiment analysis based novel opinion mining algorithms for electronic opinion analysis and computerized statistics based mathematical algorithms for electronic data analysis as well as MySQL database integration for faster data processing and cognitive ergonomics system interface for user friendly interface navigation.…”
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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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Potential norms detection in social agent societies
Published 2023“…In this paper, we propose a norms mining algorithm that detects a domain's potential norms, which we called the Potential Norms Mining Algorithm (PNMA). …”
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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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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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Building norms-adaptable agents from Potential Norms Detection Technique (PNDT)
Published 2023“…This technique enables an agent to update its norms even in the absence of sanctions from a third-party enforcement authority as found in some work, which entail sanctions by a third-party to detect and identify the norms. The PNDT consists of five components: agent's belief base; observation process; Potential Norms Mining Algorithm (PNMA) to detect the potential norms and identify the normative protocol; verification process, which verifies the detected potential norms; and updating process, which updates the agent's belief base with new normative protocol. …”
Short Survey -
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Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC)
Published 2006“…Results showed that the developed FDD algorithm successfully detect and diagnosed the pre-designed faults. …”
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Monograph -
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Datasets Size: Effect on Clustering Results
Published 2013“…This gives a wider acceptance to data mining, being an interdisciplinary field that implements algorithm on stored data with a view to discovering hidden knowledge. …”
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Conference or Workshop Item -
15
Shape-based Road Sign Detection and Recognition for Embedded Application Using MATLAB
Published 2010“…The algorithm is based on the Hough transform method to detect lines in order to identify and determine the shape of the road sign. …”
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Conference or Workshop Item -
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…The best algorithm will not be the same for all the data sets. …”
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Book Section -
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Building norms-adaptable agents from Potential Norms Detection Technique (PNDT)
Published 2013“…This technique enables an agent to update its norms even in the absence of sanctions from a third-party enforcement authority as found in some work, which entail sanctions by a third-party to detect and identify the norms. The PNDT consists of five components: agent’s belief base; observation process; Potential Norms Mining Algorithm (PNMA) to detect the potential norms and identify the normative protocol; verification process, which verifies the detected potential norms; and updating process, which updates the agent’s belief base with new normative protocol. …”
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MotionSure: a cloud-based algorithm for detection of injected object in data in motion
Published 2017“…Total 1600 different type of files were used for evaluation of the proposed algorithm, results show that 87% of injected objects were correctly detected…”
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Proceeding Paper -
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A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising
Published 2015“…A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. …”
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