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Exploring Sentiment Analysis using Different Machine Learning Algorithms on Dialectal Arabic
Published 2021“…The study explores sentiment analysis using different machine learning algorithms on dialectal Arabic text dataset. In this study, we used twitter as our data source. …”
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143
Using machine learning algorithm for detection of cyber-attacks in cyber physical systems
Published 2022“…We present the new framework for the detection of cyberattacks, which makes use of AI and ML. We begin a process to cleaning up the data in the CPS database by applying normalization to eliminate errors and duplication. …”
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144
Application of Machine Learning Algorithms to Enhance Money Laundering and Financial Crime Detection
Published 2011“…In order to analyze the performance of machine learning algorithms, data was provided by a bank to be used for educational purposes and shall remain undisclosed. …”
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145
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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GIJA:Enhanced geyser‐inspired Jaya algorithm for task scheduling optimization in cloud computing
Published 2024“…The motivation for this research stems from the increasing demand for efficient resource utilization and task management in cloud computing, driven by the proliferation of Internet of Things (IoT) devices and the growing reliance on cloud‐based services. …”
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148
A flexible genetic algorithm-fuzzy regression approach for forecasting: The case of bitumen consumption
Published 2019“…Design/methodology/approach In the proposed approach, the parameter tuning process is performed on all parameters of genetic algorithm (GA), and the finest coefficients with minimum errors are identified. …”
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149
Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands
Published 2020“…A novel evolving solution based on flower pollination algorithm is also proposed to solve the problem optimally. …”
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Prediction the performance of multistage moving bed biological process using artificial neural network (ANN)
Published 2020“…To cope with this difficult task and perform an effective and well-controlled BP operation, an artificial neural network (ANN) algorithm was developed to simulate, model, and control a three-stage (anaerobic/anoxic and MBBR) enhanced nutrient removal biological process (ENR-BP) challenging real wastewater. …”
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153
Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications
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154
KNNOR: An oversampling technique for imbalanced datasets
Published 2021“…The proposed technique called K-Nearest Neighbor OveRsampling approach (KNNOR) performs a three step process to identify the critical and safe areas for augmentation and generate synthetic data points of the minority class. …”
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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks
Published 2025“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …”
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A novel encryption algorithm using multiple semifield S-boxes based on permutation of symmetric group
Published 2023“…The presented algorithm is mainly based on the Shannon idea of substitution–permutation network where the process of substitution is performed by the proposed S<sub>8</sub> semifield substitution boxes and permutation operation is performed by the binary cyclic shift of substitution box transformed data. …”
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Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images
Published 2022“…Over the decade, numerous artificial neural network (ANN)-based techniques were adopted in order to diagnose and classify breast cancer due to the unique characteristics of learning key features from complex data via a training process. However, these schemes have limitations like slow convergence and longer training time. …”
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