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Finetuning Analytics Information Systems for a Better Understanding of Users: Evidence of Personification Bias on Multiple Digital Channels
Published 2023“…The results show that despite using the same data and algorithm, varying the number of personas strongly biases the information system’s personification of the user population. …”
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Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment
Published 2022Subjects: -
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A Robust Deep Learning Approach for Distribution System State Estimation with Distributed Generation
Published 2023“…The algorithms are tested on three different networks. The proposed approach solves the DSSE problem with limited measurements as inputs, which cannot be solved using conventional state estimation methods. …”
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masterThesis -
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Exploring Semi-Supervised Learning Algorithms for Camera Trap Images
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doctoralThesis -
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An efficient approach for textual data classification using deep learning
Published 2022“…<p dir="ltr">Text categorization is an effective activity that can be accomplished using a variety of classification algorithms. In machine learning, the classifier is built by learning the features of categories from a set of preset training data. …”
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LDSVM: Leukemia Cancer Classification Using Machine Learning
Published 2022“…This study proposes a novel method using machine learning algorithms based on microarrays of leukemia GSE9476 cells. …”
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Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm
Published 2024“…The mathematical design and methodology of the complete PV system were detailed in our prior research, titled "Dynamic and Adaptive Maximum Power Point Tracking Using Sequential Monte Carlo Algorithm for Photovoltaic System" by Odat et al. (2023) [1]. …”
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A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation
Published 2021“…<p>This paper proposes a novel fault detection and diagnosis (FDD) technique for grid-tied PV systems. The proposed approach deals with system uncertainties (current/voltage variability, noise, measurement errors, ⋯) by using an interval-valued data representation, and with large-scale systems by using a dataset size-reduction framework. …”
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An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting
Published 2021Subjects: -
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An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study
Published 2024“…We aimed to develop an app using a comprehensive geomapping navigation and estimation system based on machine learning algorithms. …”
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Deep learning-based user experience evaluation in distance learning
Published 2023“…Long short term memory-based sentiment analysis model using word2vec embedding was used to evaluate the opinions of Twitter users during distance education and also, a topic model using the LDA algorithm was built to identify the discussed topics in Twitter. …”
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Simultaneous stabilization of multimachine power systems viagenetic algorithms
Published 1999“…This paper demonstrates the use of genetic algorithms for the simultaneous stabilization of multimachine power systems over a wide range of operating conditions via single-setting power system stabilizers. …”
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78
A Survey of Data Clustering Techniques
Published 2023“…To effectively analyze and utilize this data, AI particularly machine learning, and deep learning, can provide a practical solution. …”
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masterThesis -
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A Non-convex Economic Load Dispatch Using Hybrid Salp Swarm Algorithm
Published 2021“…In this paper, the economic load dispatch (ELD) problem with valve point effect is tackled using a hybridization between salp swarm algorithm (SSA) as a population-based algorithm and β-hill climbing optimizer as a single point-based algorithm. …”
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