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machine algorithm » cosine algorithm (Expand Search)
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On the protection of power system: Transmission line fault analysis based on an optimal machine learning approach
Published 2022“…The design is carried out based on the selection of the optimal model parameters using a search optimization algorithm called GridSearchCV. …”
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Machine learning based approaches for intelligent adaptation and prediction in banking business processes. (c2018)
Published 2018“…In this context, the notion of integrating machine learning techniques in banking business processes has emerged, where trainable computational algorithms can be improved by learning. …”
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Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study
Published 2024“…</p><h3>Objective</h3><p dir="ltr">In this paper, we propose a machine learning–based approach for identifying research gaps through the analysis of scientific literature. …”
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Blue collar laborers’ travel pattern recognition: Machine learning classifier approach
Published 2021“…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. …”
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Development of Lévy flight-based reptile search algorithm with local search ability for power systems engineering design problems
Published 2022“…The superiority of the proposed Lévy flight-based reptile search and Nelder-Mead (L-RSANM) algorithm-based PID controller for the AVR system is demonstrated comparatively using convergence, statistical and nonparametric tests along with transient and frequency responses. …”
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Wind, Solar, and Photovoltaic Renewable Energy Systems with and without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques
Published 2022“…This paper covered the most resent and important researchers in the domain of renewable problems using the learning-based methods. Various types of Deep Learning (DL) and Machine Learning (ML) algorithms employed in Solar and Wind energy supplies are given. …”
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A systematic review of recent advances in the application of machine learning in membrane-based gas separation technologies
Published 2024“…This study aims to bridge this gap by comprehensively reviewing ML concepts, approach, and algorithms in the <u>membrane separation</u> sector. …”
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Thermal Change Index-Based Diabetic Foot Thermogram Image Classification Using Machine Learning Techniques
Published 2022“…Classical machine learning algorithms with feature engineering and the convolutional neural network (CNN) with image enhancement techniques were extensively investigated to identify the best performing network for classifying thermograms. …”
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Monitoring Bone Density Using Microwave Tomography of Human Legs: A Numerical Feasibility Study
Published 2021“…This study was performed using an in-house finite-element method contrast source inversion algorithm (FEM-CSI). …”
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A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network
Published 2019“…The reported accuracy dramatically outperforms the previous algorithms, including gradient tree boosting (GTB), random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and linear discriminant analysis (LDA). …”
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A machine learning model for early detection of diabetic foot using thermogram images
Published 2021“…However, the distribution of plantar temperature may be heterogeneous, making it difficult to quantify and utilize to predict outcomes. We have compared a machine learning-based scoring technique with feature selection and optimization techniques and learning classifiers to several state-of-the-art Convolutional Neural Networks (CNNs) on foot thermogram images and propose a robust solution to identify the diabetic foot. …”
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Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches
Published 2024“…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”
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