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181
Android Malware Detection Using Machine Learning
Published 2024“…This paper presents a machine learning approach for Android malware detection. In this work, several machine learning algorithms were utilized, namely k-Nearest neighbor (KNN), Decision Trees (DT), Naive Bayes (NB), Support Vector Machine (SVM) and other ensemble classifiers including Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LGBM) and CatBoost. …”
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182
The maximum common subgraph problem
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FarmTech: Regulating the use of digital technologies in the agricultural sector
Published 2023“…<p dir="ltr">Farming relies on the accurate collection and processing of data. Algorithms utilizing artificial intelligence can predict patterns and spot problems, helping farmers make more informed decisions. …”
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185
A Hash-Based Assessment and Recovery Algorithm for Distributed Healthcare Systems Using Blockchain Technology
Published 2020“…Numerous damage assessment and recovery algorithms have been proposed in the literature. In this work, we present a distributed algorithm that uses blockchain technology and hash tables to solve the information warfare problem in healthcare systems. …”
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186
An Optimized Feature Selection Technique in Diversified Natural Scene Text for Classification Using Genetic Algorithm
Published 2021“…The Support Vector Machine (SVM) algorithm is used for classification and the average F-Score is used as fitness function and target condition. …”
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187
Artificial intelligence-based methods for fusion of electronic health records and imaging data
Published 2022“…In our analysis, a typical workflow was observed: feeding raw data, fusing different data modalities by applying conventional machine learning (ML) or deep learning (DL) algorithms, and finally, evaluating the multimodal fusion through clinical outcome predictions. …”
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188
Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT
Published 2021“…This paper proposes an Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT. …”
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189
Empowering IoT Resilience: Hybrid Deep Learning Techniques for Enhanced Security
Published 2024“…The time efficiency of both proposed algorithms renders them well-suited for deployment in IoT ecosystems. …”
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190
Design of adaptive arrays based on element position perturbations
Published 1993“…The main advantage of using this technique over the other commonly used methods is that the amplitudes and phases of the array elements can be used mainly to steer the main beam towards the desired signal. …”
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An Improved Genghis Khan Optimizer based on Enhanced Solution Quality Strategy for Global Optimization and Feature Selection Problems
Published 2024“…The algorithm presented aims to solve the FS problem and has been assessed using benchmark optimization problems from the CEC’2017 and CEC’2022. …”
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Fuzzy Logic Adaptive Crow Search Algorithm for MPPT of a Partially Shaded Photovoltaic System
Published 2024“…<p dir="ltr">The arbitrary selection of the Crow Search Algorithm (CSA) parameters, the Awareness Probability (AP) and the Flight Length (fl) results in poor convergence performance and efficiency even if the CSA performs well when solving global optimization problems. …”
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196
Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation
Published 2023“…This study proposes a novel nature-inspired meta-heuristic optimizer based on the Reptile Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray-scale multi-level thresholding, called RSA-SSA. …”
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197
An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting
Published 2021Subjects: -
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Just-in-time defect prediction for mobile applications: using shallow or deep learning?
Published 2023“…In this research, we evaluate the performance of traditional machine learning algorithms and data sampling techniques for JITDP problems and compare the model performance with the performance of a DL-based prediction model. …”
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Blue collar laborers’ travel pattern recognition: Machine learning classifier approach
Published 2021“…A pattern recognition model is applied to a revealed preference (RP) survey obtained from the Ministry of Transportation and Communication (MoTC) in Qatar for the travel diary for blue-collar workers. Raw data preprocessing and outliers detection and filtering algorithms were applied at the first stage of the analysis, and consequently, an activity-based travel matrix was developed for each household. …”