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TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection
Published 2020“…TIDCS reduces the number of features in the input data based on a new algorithm for feature selection. …”
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Parameter Estimation Of Wiener-Hammerstein Models Via Genetic Algorithms
Published 2020“…In this paper, a modified genetic algorithm is used as a procedure to solve the parameter identification problem of the nonlinear Wiener-Hammerstein models. …”
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A genetic-based algorithm for fuzzy unit commitment model
Published 2000“…The genetic algorithm (GA) approach is then used to solve the proposed fuzzy UCP model. …”
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Combining and adapting software quality predictive models by genetic algorithms
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Optimization of Piezoelectric Sensor-Actuator for Plate Vibration Control Using Evolutionary Computation: Modeling, Simulation and Experimentation
Published 2021“…Both disturbance and control signal acting on the plate is created by using piezoelectric (PZT) patches. The analytical model is derived based on the Euler-Bernoulli model. …”
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Predict Student Success and Performance factors by analyzing educational data using data mining techniques
Published 2022“…The model is then applied to data collected from a reputable university that included 126,698 records with twenty-six (26) initial data attributes. …”
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Gas Metal Arc Welding (GMAW) Process Optimization Using Machine Learning Models
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Predicting Plasma Vitamin C Using Machine Learning
Published 2022“…The low R-squared scores obtained by the models are likely to be due to the low resolution of the NHANES data, particularly the dietary data. …”
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024“…<p>Feature selection (FS) is a crucial technique in machine learning and data mining, serving a variety of purposes such as simplifying model construction, facilitating knowledge discovery, improving computational efficiency, and reducing memory consumption. …”
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Brain Source Localization in the Presence of Leadfield Perturbations
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Privacy-Preserving Fog Aggregation of Smart Grid Data Using Dynamic Differentially-Private Data Perturbation
Published 2022“…We describe our differentially-private model with flexible constraints and a dynamic window algorithm to maintain the privacy-budget loss in infinitely generated time-series data. …”
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Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms
Published 2022“…The values are 18.44 % and 23.9 % for CV-RMSE, 11.6 % and 10.06 % for MAPE, and 7.5 % and 6.75 % for MdAPE, using ANN and GP, respectively. While the previous studies mostly used ANN to demonstrate the capability of MLs to predict PG over the mechanistic or correlation-based models, the present research has shown that GP is even better than ANN using a wide range of FPs and a large data set.…”
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Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches
Published 2024“…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”
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Nonlinear model predictive control of Hammerstein and Wiener modelsusing genetic algorithms
Published 2001“…In this paper a novel approach for the implementation of nonlinear MPC is proposed using genetic algorithms (GAs). The proposed method formulates the MPC as an optimization problem and genetic algorithms are used in the optimization process. …”
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