Search Results - (( evolution classifications mining algorithm ) OR ( variable detection method algorithm ))
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1
Classification of Immunosignature Using Random Forests for Cancer Diagnosis
Published 2015“…To attain this essential research purpose, a minimum set of genes that can assure higher performance in classification using data mining algorithms need to be detected. …”
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Proceeding Paper -
2
Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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3
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 -
4
Y-type Random 2-satisfiability In Discrete Hopfield Neural Network
Published 2024“…Additionally, the proposed Hybrid Differential Evolution Algorithm was implemented into the training phase to ensure that the cost function of the Discrete Hopfield Neural Network is minimized. …”
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5
Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…The results obtained from the simulation study and real data sets indicate that the proposed method possesses high detection power with minimal misclassification error compared to the MRCD and MDP methods. …”
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6
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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7
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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8
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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9
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 -
10
A real time road marking detection system on large variability road images database
Published 2017“…One of the first embedded system is a lane detection system, which was implemented using road marking detection algorithms with the aim to produce a system that is able to detect various shapes of road markings on the images that are captured under various imaging conditions. …”
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Conference or Workshop Item -
11
Coronary artery stenosis detection and visualization / Tang Sze Ling
Published 2015“…In contrast to the conventional methods which perform detection from a single image, the stenosis detection algorithm using two images from various view angles to avoid false positive (stenosis overestimated) and false negative (stenosis underestimated). …”
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12
Multi road marking detection system for autonomous car using hybrid- based method
Published 2018“…The proposed system consists of a combination of Inverse Perspective Transform method, an image enhancement method and edge detection method. …”
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13
Application of data mining techniques for economic evaluation of air pollution impact and control
Published 2007“…For that purpose, we use data mining techniques. Data mining techniques applied in this thesis were: 1) Group method of data handling (GMDH), originally from engineering, introducing principles of evolution - inheritance, mutation and selection - for generating a network structure systematically to develop the automatic model, synthesis, and its validation; 2) The weighted least square (WLS) and step wise regression were also applied for some cases; 3) The classification-based association rules were applied. …”
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14
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 -
15
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 -
16
Integrated face detection approach for far image application
Published 2016“…The noise reduction method in the proposed algorithm consists of a combination of a morphological filter and a rejection method. …”
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17
Image Based Congestion Detection Algorithms And Its Real Time Implementation
Published 2015“…The proposed system uses a fast and reliable method to detect traffic congestions. The methodology includes vehicle detection by using backlight pairing feature algorithm and modified Watershed algorithm. …”
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18
Fault detection and diagnosis for gas density monitoring using multivariate statistical process control
Published 2011“…Results show that method based on PCA and PCorrA was able to detect the pre-designed faults successfully and identify variables which cause the faults.…”
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Article -
19
Automated QT interval measurement using modified Pan-Tompkins algorithm with independent isoelectric line approach
Published 2020“…This method uses an improved Pan-Tompkins algorithm from the previous work with independent of the isoelectric line approach for detecting the QRS onset and the T offset. …”
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Article -
20
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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