Search Results - (( evolution extraction method algorithm ) OR ( variable detection machine algorithm ))
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Parameter extraction of photovoltaic module using hybrid evolutionary algorithm
Published 2023“…Algorithms; Diodes; Extraction; Iterative methods; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Different evolutions; Differential Evolution; Diode modeling; Electromagnetism-like algorithm; Extracting parameter; Hybrid evolutionary algorithm; Photovoltaic model; Photovoltaic modules; Evolutionary algorithms…”
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Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm
Published 2023“…Algorithms; Diodes; Errors; Extraction; Iterative methods; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Differential evolution algorithms; Diode modeling; Electromagnetism-like algorithm; Fast convergence speed; Hybrid evolutionary algorithm; IV characteristics; Photovoltaic model; Root mean square errors; Evolutionary algorithms…”
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A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model
Published 2023“…Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system…”
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Pure intelligent monitoring system for steam economizer trips
Published 2023“…Economizers; Failure (mechanical); Fault detection; Knowledge acquisition; Learning algorithms; Learning systems; Neural networks; Plant shutdowns; Steam; Thermoelectric power plants; Extreme learning machine; Fault detection and diagnosis systems; Intelligent modeling; Intelligent monitoring systems; Network methodologies; Operational conditions; Operational variables; Thermal power plants; Steam power plants…”
Conference Paper -
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Parameter extraction of solar photovoltaic modules using penalty-based differential evolution
Published 2012“…The two diode model of a solar cell is used as the basis for the extraction problem. The analyses carried out using synthetic current-voltage (I-V) data set showed that the proposed P-DE outperforms other Evolutionary Algorithm methods, namely the simulated annealing (SA), genetic algorithm (GA), and particle swarm optimization (PSO). …”
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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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Thesis -
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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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Automated detection and evaluation of ischemic stroke on ct brain imaging using machine learning techniques
Published 2025“…This study investigates the application of machine learning algorithms for the detection of ischemic stroke using CT brain images. …”
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Application of machine learning algorithms to predict the thyroid disease risk: an experimental comparative study
Published 2022“…For this reason, this study compares eleven machine learning algorithms to determine which one produces the best accuracy for predicting thyroid risk accurately. …”
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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 -
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Detection of Denial of Service Attacks against Domain Name System Using Neural Networks
Published 2009“…In the current research for our machine learning engine, we aimed to find the optimum machine learning algorithm to be used as an IDS. …”
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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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Investigation of fault detection and isolation accuracy of different Machine learning techniques with different data processing methods for gas turbine
Published 2022“…The present study investigates the accuracy of different machine learning classification algorithms with three different data smoothing techniques for gas turbine fault detection and isolation task. …”
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Investigation of fault detection and isolation accuracy of different Machine learning techniques with different data processing methods for gas turbine
Published 2022“…The present study investigates the accuracy of different machine learning classification algorithms with three different data smoothing techniques for gas turbine fault detection and isolation task. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat
Published 2021“…Readability was detected using a free online optical character recognition application called Aeosoft. Size was extracted using Extreme Point Detection algorithm and Hit or Miss Transformation method was used to extract the stroke formation pattern. …”
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Development of sorting system for oil palm in vitro shoots using machine vision approach
Published 2014“…Ultimately, the sorting algorithm performance came to be evaluated by support vector machine algorithm. …”
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Predictive Modelling of Stroke Occurrence among Patients using Machine Learning
Published 2023“…Advanced machine learning algorithms, including logistic regression, decision trees, random forests, and support vector machines, were utilized to analyses the dataset and develop a predictive model. …”
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