Search Results - (( parameter deviation detection algorithm ) OR ( java implementation learning algorithm ))
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1
Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm
Published 2008“…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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2
Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…This research focuses on the parameter estimation, outlier detection and imputation of missing values in a linear functional relationship model (LFRM). …”
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3
The multiple outliers detection for circular univariate data using different agglomerative clustering algorithms
Published 2024“…Meanwhile, SL-Satari/Di, CL-Satari/Di, and AL-Satari/Di algorithms are recommended to be used for large sample sizes since these algorithms perform very well in detecting the outliers and have low masking and swamping effect at any percentage of outliers and concentration parameter. …”
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4
An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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5
Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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6
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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7
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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8
Comparative study of clustering-based outliers detection methods in circularcircular 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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9
Fault detection and diagnosis using rule-based support system on fatty acid fractionation column
Published 2003“…Process variables are defined as fault if they are deviated outside this region. 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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10
A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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11
Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…To rectify this problem, we propose a Dynamic Robust Bootstrap-LTS based (DRBLTS) algorithm where the percentage of outliers in each bootstrap sample is detected. …”
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12
Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…This study focuses on the parameter estimation and outlier detection for some types of the circular model. …”
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13
Antifriction Bearing Malfunction Detection and Diagnostics using Hybrid Approach
Published 2018“…The vibration signals were obtained from Case Western Reserve University. An algorithm is developed for abnormal condition detection and diagnostics using intelligent systems. …”
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14
Fault diagnostic advisory system using moving-range chart and hazard operability study.
Published 2007“…The advisory system has successfully detected and diagnosed the deviations and displayed the causes and consequences of the faults. …”
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15
Antifriction Bearing Malfunction Detection and Diagnostics using Hybrid Approach
Published 2018“…The vibration signals were obtained from Case Western Reserve University. An algorithm is developed for abnormal condition detection and diagnostics using intelligent systems. …”
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16
Fault diagnostic advisory system using moving-range chart and hazard operability study
Published 2007“…The advisory system has successfully detected and diagnosed the deviations and displayed the causes and consequences of the faults. …”
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17
Add-on anomaly threshold technique for improving unsupervised intrusion detection on SCADA data
Published 2020“…The proposed technique can be used for any unsupervised anomaly detection approach to mitigate the sensitivity of such parameters and improve the performance of the SCADA unsupervised anomaly detection approaches. …”
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18
Reactive approach for automating exploration and exploitation in ant colony optimization
Published 2016“…RACO can be used in providing a dynamic exploration and exploitation mechanism, setting a parameter value which allows an efficient search, describing the amount of exploration an ACO algorithm performs and detecting stagnation situations.…”
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19
Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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20
An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning
Published 2019“…The experiment on noisy data stream shows that BOCEDS algorithm can detect noise with an accuracy of approximately 100%. …”
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