Search Results - (( variable selection based algorithm ) OR ( variable detection using algorithm ))
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1
Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…Sure screening-based correlation methods are popular tools used to select the most significant variables in the true model in sparse and high dimensional analysis. …”
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Thesis -
2
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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3
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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4
Artificial immune system based on real valued negative selection algorithms for anomaly detection
Published 2015“…This shows that the Negative Selection Algorithms are equipped with the capabilities of detecting changes in data, thus appropriate for anomaly detection. …”
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5
Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…Identification studies using NARX (Nonlinear AutoRegressive with eXogenous input) models employing simulated systems and real plant data are used to demonstrate that the algorithm is able to detect significant variables and terms faster and to select a simpler model structure than other well-known EC methods.…”
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6
Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC)
Published 2006“…In this research work, an FDD algorithm is developed using MSPC and correlation coefficients between process variables. …”
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Monograph -
7
Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…The correlation of each system calls are examined using coefficient correlations of each selected system call variables. …”
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8
Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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9
An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection
Published 2018“…Real-Valued Negative Selection Algorithm with Variable-Sized Detectors (V-Detectors) is an offspring of AIS and demonstrated its potentials in the field of anomaly detection. …”
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10
Cluster head selection using fuzzy logic and chaotic based genetic algorithm in wireless sensor network
Published 2013“…Then, the number and place of cluster heads are determined in base station by using genetic algorithm based on chaotic. Our simulation results in the NS-2 show the longer network lifetime of the proposed algorithm than the LEACH, DEEC, SEDEEC and GFS protocols.…”
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11
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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12
Extremal region detection and selection with fuzzy encoding for food recognition
Published 2019“…The second algorithm reduces the quantity of interest regions by using the Extremal Region Selection (ERS) algorithm. …”
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13
ECG-based driving fatigue detection using heart rate variability analysis with mutual information
Published 2023“…The results of the experiments show that the random forest algorithm with 44 selected features produced the best model performance testing accuracy of 95.45%, with cross-validated accuracy of 98.65%.…”
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14
Multidimensional Minimization Training Algorithms for Steam Boiler Drum Level Trip Using Artificial Intelligence Monitoring System
Published 2010“…This paper deals with the Fault Detection and Diagnosis of steam boiler drum low level by artificial Neural Networks using two different interpretation algorithms. …”
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15
Fault diagnostic advisory system using moving-range chart and hazard operability study.
Published 2007“…Although the scheme was developed based on 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 study for each selected monitoring variables.…”
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16
A study on advanced statistical analysis for network anomaly detection
Published 2005“…The correlation of each system calls are examined using coefficient correlations of each selected system call variables. …”
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Monograph -
17
Optimized differential evolution algorithm for linear frequency modulation radar signal denoising
Published 2013“…We propose an optimized crossover scheme that changes the crossover operation from being fixed-length to random-length, which has been designed to fit for the proposed variable length DE. We refer to the new DE algorithm as random variable length crossover DE (rvlx- DE) algorithm. …”
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18
Fault diagnostic advisory system using moving-range chart and hazard operability study
Published 2007“…Although the scheme was developed based on 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 study for each selected monitoring variables…”
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Article -
19
Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This improved algorithm, known as the edge-template Contour Delineation (etCD), is based on the fusion of edge detection with corner-template detection and dynamic thresholding to produce enhanced edge map. …”
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20
Gene Selection For Cancer Classification Based On Xgboost Classifier
Published 2022“…XGBoost Classifier is applied in this research, which it is an efficient open-source implementation of the gradient boosted trees algorithm. Gradient boosting is a supervised learning algorithm, which attempts to accurately predict a target variable by combining the estimates of a set of simplifier, weaker models. …”
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