Search Results - (( deviation detection based algorithm ) OR ( using optimization based algorithm ))
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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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Reactive approach for automating exploration and exploitation in ant colony optimization
Published 2016“…Ant colony optimization (ACO) algorithms can be used to solve nondeterministic polynomial hard problems. …”
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An enhanced sequential exception technique for semantic-based text anomaly detection
Published 2019“…If these challenges are not properly resolved, identifying semantic-based text anomaly will be less accurate. This study proposes an Enhanced Sequential Exception Technique (ESET) to detect semantic-based text anomaly by achieving five objectives: (1) to modify Sequential Exception Technique (SET) in processing unstructured text; (2) to optimize Cosine Similarity for identifying similar and dissimilar text data; (3) to hybridize modified SET with Latent Semantic Analysis (LSA); (4) to integrate Lesk and Selectional Preference algorithms for disambiguating senses and identifying text canonical form; and (5) to represent semantic-based text anomaly using First Order Logic (FOL) and Concept Network Graph (CNG). …”
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Metacarpal phantom radiograph edge detection using genetic algorithm gradient based genotype / Norharyati Md Ariff
Published 2007“…It is need to get the optimal result of osteoperosis or osteopenia detection. …”
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GENETIC FUZZY FILTER BASED ON MAD AND ROAD TO REMOVE MIXED IMPULSE NOISE
Published 2010“…The proposed method consists of three components, including fuzzy noise detection system, fuzzy switching scheme filtering, and fuzzy parameters optimization using genetic algorithms (GA) to perform efficient and effective noise removal. …”
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Enhanced Image Classification for Defect Detection on Solar Photovoltaic Modules
Published 2023“…The second algorithm uses K Nearest Neighbour using a ratio of training data and testing data of 95:05 resulting in an accuracy value of 62%. …”
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Development Of Two New Auxiliary Information Control Charts, And Economic And Economic-Statistical Designs Of Several Auxiliary Information Control Charts
Published 2020“…The first objective of this thesis is to develop the run sum X - AI (RS X - AI) chart for monitoring the process mean. Optimal parameters computed using the optimization algorithms developed and the step-by-step approach for constructing the optimal RS - AI chart are provided in this thesis. …”
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Mental Stress Classification Among Higher Education Students In Malaysia From Electroencephalogram (Eeg) Using Convolutional Neural Network With Modified Stochastic Gradient D...
Published 2024“…The chosen algorithm, 1D-CNN, was modified using a tailored SGD optimizer that incorporates momentum and learning rate decay to improve convergence and address challenges like vanishing gradients. …”
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Sensing texture using an artificial finger and a data analysis based on the standard deviation
Published 2015“…For the automatic control of an artificial hand and to feedback information to the amputee, an algorithm has been developed based on the standard deviation of signal data from the sensor. …”
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A smart spectrum access technique for dynamic multi-hop routing in cognitive radio-based disaster response networks
Published 2022“…The multi-hop route selection is executed using the Hybrid Spiral Penguin Optimization (HSPO) algorithm based on the decision made by the DE-D2PG. …”
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Deviation detection in text using conceptual graph interchange format and error tolerance dissimilarity function
Published 2012“…This paper focuses on a graph-based approach for text representation and presents a novel error tolerance dissimilarity algorithm for deviation detection. …”
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Sensing texture using an artificial finger and a data analysis based on the standard deviation
Published 2015“…For the automatic control of an artificial hand and to feedback information to the amputee, an algorithm has been developed based on the standard deviation (SD) of signal data from the sensor. …”
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Development of a rule-based fault diagnostic advisory system for precut fractionation column
Published 2005“…The advisory system algorithm used process history based method and presented by rule-based approach. …”
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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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Improving the synthetic coefficient of variation chart by incorporating side sensitivity
Published 2024“…Based on the results obtained which had been validated using simulations, the proposed side-sensitive synthetic-y chart outperformed the Shewhart-y chart, the EWMA-y2 chart and the existing synthetic-y chart without the side sensitivity feature for most cases and displayed a significant improvement. …”
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The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model
Published 2017“…In this study, we proposed multiple outliers detection in circular regression models based on the clustering algorithm. …”
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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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Development of a computer vision-based technique for analysis of hand therapy exercise
Published 2018“…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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Comparative study of clustering-based outliers detection methods in circular-circular regression model
Published 2021“…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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