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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
منشور في 2022"…To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …"
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The buffered work-pool approach for search-tree based optimization algorithms
منشور في 2017"…This new trend has been motivated by hardness of approximation results that appeared in the last decade, and has taken a great boost by the emergence of parameterized complexity theory. Exact algorithms often follow the classical search-tree based recursive backtracking strategy. …"
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احصل على النص الكامل
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Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network
منشور في 2024"…Computational techniques, like the finite element method, are used to analyse behaviours based on varied input parameters. …"
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A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem
منشور في 2020"…This paper presents a new algorithm based on integrating the use of genetic algorithms and tabu search methods to solve the unit commitment problem. …"
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Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering
منشور في 2022"…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. …"
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AI and IoT-based concrete column base cover localization and degradation detection algorithm using deep learning techniques
منشور في 2023"…This paper proposes a novel automated algorithm for the health monitoring of concrete column base cover degradation based on IoT and the state-of-the-art deep learning framework, Convolutional Neural Network (CNN). …"
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Predicting Dropouts among a Homogeneous Population using a Data Mining Approach
منشور في 2019"…Our research relies solely on pre-college and college performance data available in the institutional database. Our research reveals that the Gradient Boosted Trees is a robust algorithm that predicts dropouts with an accuracy of 79.31% and AUC of 88.4% using only pre-enrollment data. …"
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Methodology for Analyzing the Traditional Algorithms Performance of User Reviews Using Machine Learning Techniques
منشور في 2020"…Based on the semantics of reviews of the applications, the results of the reviews were classified negative, positive or neutral. In this research, different machine-learning algorithms such as logistic regression, random forest and naïve Bayes were tuned and tested. …"
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Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology
منشور في 2023"…In this study, the emergency control algorithms based on ensemble machine learning algorithms (XGBoost and Random Forest) were developed for a low-inertia power system. …"
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Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms
منشور في 2021"…We also developed a binary template matching-based algorithm, which gives 93.64% accuracy 6X faster. …"
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Real-Time Selective Harmonic Mitigation Technique for Power Converters Based on the Exchange Market Algorithm
منشور في 2020"…The performance of the EMA-based SHM is presented showing experimental results considering a reduced number of switching angles applied to a specific three-level converter, but the method can be extrapolated to any other three-level converter topology.…"
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Sample intelligence-based progressive hedging algorithms for the stochastic capacitated reliable facility location problem
منشور في 2024"…To manage uncertainty and decide effectively, stochastic programming (SP) methods are often employed. Two commonly used SP methods are approximation methods, i.e., Sample Average Approximation (SAA), and decomposition methods, i.e., Progressive Hedging Algorithm (PHA). …"
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A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network
منشور في 2019"…In order to address this issue, in this paper, we propose a novel hybrid approach with both convolutional and recurrent neural networks combined, which is based on the long short-term memory module. Featuring the capability of learning the correlations of time-series data, the proposed deep learning method is well-suited for extracting the valuable transient feature contained in the very beginning of the response curve. …"
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Assessment of Drug-Induced QTc Prolongation in Mental Health Practice: Validation of an Evidence-Based Algorithm
منشور في 2023"…</p></h3><h3>Methods</h3><h3><p dir="ltr">Following an initial face validity by content experts, a cross-sectional survey of mental health care practitioners with a 4-point Likert-type scale was used to assess the validity of the decision steps on the QTcIP algorithm (QTcIPA) by estimating the content validity index (CVI) and the modified kappa statistic (κ*). …"
