Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands by Peng, Wang

“…An IEEE standard test system is used as the hybrid AC/DC microgrid case study to assess the performance of proposed model.…”
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Graph Computing Systems and Partitioning Techniques: A Survey by Tewodros Alemu Ayall (19273717)

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An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting by Mohamed Massaoudi (16888710)

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Using genetic algorithms to optimize software quality estimation models by Azar, Danielle

“…In the first approach, we assume the existence of several models, and we use a genetic algorithm to combine them, and adapt them to a given data set. …”
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Second-order conic programming for data envelopment analysis models by Mourad, Nahia

“…This paper constructs a second-order conic optimization problem unifying several DEA models. Moreover, it presents an algorithm that solves the former problem, and provides a MATLAB function associated with it. …”
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Performance Modeling of Rooftop PV Systems in Arid Climate, a Case Study for Qatar: Impact of Soiling Losses and Albedo Using PVsyst and SAM by Sachin Jain (19161721)

“…To overcome these limitations, the Humboldt State University (HSU) soiling model was calibrated using field measurements from a DustIQ sensor, and its parameters, rainfall cleaning threshold and particulate deposition velocity were optimized through a Differential Evolution algorithm. …”

UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data by Behrouz Ahadzadeh (19757022)

“…<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. …”

A Multiprocessing-Based Sensitivity Analysis of Machine Learning Algorithms for Load Forecasting of Electric Power Distribution System by Ameema Zainab (16864263)

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Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms by Arafat Rahman (8065562)

Nonlinear model predictive control of Hammerstein and Wiener modelsusing genetic algorithms by Al-Duwaish, H.

“…Application to two types of nonlinear models namely Hammerstein and Wiener Models is studied and the simulation results are shown for the case of two chemical processes to demonstrate the performance of the proposed scheme…”
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A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models by Azar, Danielle

“…In this paper, we present a genetic algorithm that adapts such models to new data. We give empirical evidence illustrating that our approach out-beats the machine learning algorithm C4.5 and random guess.…”
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Correlation Clustering with Overlaps by Fakhereldine, Amin

“…In other words, data elements (or vertices) will be allowed to be members in more than one cluster instead of limiting them to only one single cluster, as in classical clustering methods. …”
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Exploratory risk prediction of type II diabetes with isolation forests and novel biomarkers by Yousef, Hibba

“…In particular, Isolation Forest (iForest) was applied as an anomaly detection algorithm to address class imbalance. iForest was trained on the control group data to detect cases of high risk for T2DM development as outliers. …”
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Using Machine Learning Algorithms to Forecast Solar Energy Power Output by Ali Jassim Lari (22597940)

“…The data forecasting horizon used was a 24-h window in steps of 30 min. …”

Predictive Model of Psychoactive Drugs Consumption using Classification Machine Learning Algorithms by Almahmood, Mothanna

“…Eighteen classification models were built using different classification algorithms such as Gaussian Naive Bais, Logistic Regression, k-nearest neighbors, Random Forest, and Decision Tree. …”
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A reduced model for phase-change problems with radiation using simplified PN approximations by Belhamadia, Youssef

“…The integro-differential equation for the full radiative transfer is replaced by a set of differential equations which are independent of the angle variable and easy to solve using conventional computational methods. To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. …”
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Time-varying volatility model equipped with regime switching factor: valuation of option price written on energy futures by Leduc, Guillaume

“…To determine the parameters of the regime switching model and identify when economic states change, we employ the EM algorithm, utilizing real gas futures price data. …”
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A data envelopment analysis model for opinion leaders’ identification in social networks by Hamed Baziyad (19273738)

Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning by Far, Reza Davoodi

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A hybrid heuristic approach to optimize rule based software quality estimation models. (c2008) by Korkmaz, Rita

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