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Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence
Published 2020“…One of the best algorithms in terms of the result is the Long Short Term Memory (LSTM) since it is based on recurrent neural networks which uses loop as a method to learn from heuristics data. …”
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024Subjects: -
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The unified effect of data encoding, ansatz expressibility and entanglement on the trainability of HQNNs
Published 2023“…However, the integration of quantum computing and machine learning poses several challenges. One of the prominent challenges lies in the presence of barren plateaus (BP) in QML algorithms, particularly in quantum neural networks (QNNs). …”
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Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms
Published 2022“…The accuracy of these algorithms was assessed with standard statistical measures and ground truth data randomly collected in Prince Edward Island, Canada. …”
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Estimating Construction Project Duration Using a Machine Learning Algorithm
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Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering
Published 2022Subjects: “…Data clustering…”
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Methodology for Analyzing the Traditional Algorithms Performance of User Reviews Using Machine Learning Techniques
Published 2020“…In this research, different machine-learning algorithms such as logistic regression, random forest and naïve Bayes were tuned and tested. …”
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Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization
Published 2022Subjects: “…orthogonal learning (OL)…”
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Predicting Dropouts among a Homogeneous Population using a Data Mining Approach
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Novel RFID-Based Pose Estimation Using Single Stationary Antenna
Published 2016“…This work provides an alternative and relatively cheap approach for remotely estimating the pose of an object. As a proof of concept, we justify our scheme analytically and provide numerical and experimental data to substantiate the feasibility of our methodology.…”
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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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