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using algorithm » cosine algorithm (Expand Search)
per algorithm » deer algorithm (Expand Search), rd algorithm (Expand Search), search algorithm (Expand Search)
elements per » elementi per (Expand Search), elements _ (Expand Search)
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501
Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization
Published 2023“…Although the increasing number of articles proposed to develop DTL- and DDA-based VSSs, a thorough review that summarizes and criticizes the state-of-the-art is still missing. …”
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502
Information warfare. (c2015)
Published 2015“…Numerous damage assessment and recovery algorithms have been proposed by researchers. In this work we present an efficient lightweight detection and recovery algorithm that is based on the matrix approach and that can be used to recover from malicious attacks. …”
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masterThesis -
503
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504
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505
An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection
Published 2022“…The binary enhanced RSO is built based on three successive modifications: i) an S-shape transfer function is used to develop binary RSO algorithms; ii) the local search paradigm of particle swarm optimization is used with the iterative loop of RSO to boost its local exploitation; iii) three crossover mechanisms are used and controlled by a switch probability to improve the diversity. …”
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506
A Digital DNA Sequencing Engine for Ransomware Analysis using a Machine Learning Network
Published 2020“…The data is finally classified as either ransomware or goodware using the learning methodologies. …”
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507
Identification And Weather Sensitivity Of Physically Based Model Of Residential Air-Conditioners For Direct Load Control: A Case Study
Published 2020“…An online maximum likelihood based-identification algorithm is developed. The required hardware and system instrumentation are detailed. …”
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508
Multimodal feature fusion and ensemble learning for non-intrusive occupancy monitoring using smart meters
Published 2025“…In this study, we introduce the multimodal feature fusion for non-intrusive occupancy monitoring (MMF-NIOM) framework, which leverages both classical and deep machine learning algorithms to achieve state-of-the-art occupancy detection performance using smart meter data. …”
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509
Performance Analysis of a Three-to-Five Phase Dual Matrix Converter Based on Space Vector Pulse Width Modulation
Published 2019“…<p dir="ltr">In this paper, space vector pulse width modulation (SVPWM)-based algorithms for a five-phase open-end load fed from dual matrix converter (DMC) have been proposed. …”
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510
Fault Diagnosis Based Machine Learning and Fault Tolerant Control of Multicellular Converter Used in Photovoltaic Water Pumping System
Published 2023“…<p dir="ltr">Currently, providing water in developing countries, especially in dry and hot rural areas, is a significant challenge. …”
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511
Active distribution network type identification method of high proportion new energy power system based on source-load matching
Published 2023“…Firstly, the typical daily output scenarios of DG are extracted by clustering method, and the generalized load curve model is solved by the optimization algorithm to obtain the source load operation data; Secondly, calculate the source-load matching indicators (including matching performance, matching degree, and matching rate) according to the source load data of each region, and identify the distribution network type according to the range of the index values; Finally, several indicators are introduced to quantify the characteristics of different types of distribution networks. …”
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512
Automatic Recognition of Poets for Arabic Poetry using Deep Learning Techniques (LSTM and Bi-LSTM)
Published 2024“…In our research, we introduce a comprehensive approach to Arabic poetry text classification using deep learning techniques. We have used an almost one-million record dataset of Arabic poetry verses extracted from a poetry encyclopedia. …”
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513
Cognitive Load Estimation Using a Hybrid Cluster-Based Unsupervised Machine Learning Technique
Published 2024“…In this study, we harnessed the capabilities of a four-channel, wearable EEG device that captured brain activity data during two distinct CL states: Baseline (representing a non-CL, resting state) and the Stroop Test (a CL-inducing state). …”
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514
An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure
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doctoralThesis -
515
Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test
Published 2019“…Data generated from an oral glucose tolerance test (OGTT) was used to develop a predictive model based on the support vector machine (SVM). …”
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516
Solar power forecasting beneath diverse weather conditions using GD and LM-artificial neural networks
Published 2023“…The proposed ANN based algorithm has been used for unswerving petite term forecasting. …”
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517
HVAC system attack detection dataset
Published 2021“…It aims to promote and support the research in the field of cybersecurity of HVAC systems in smart buildings by facilitating the validation of attack detection and mitigation strategies, benchmarking the performance of different data-driven algorithms, and studying the impact of attacks on the HVAC system.…”
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518
Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images
Published 2023“…In the present article, we proposed a novel transfer learning-based predictor called, Lung-EffNet for lung cancer classification. …”
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519
Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review
Published 2024“…The most widely used algorithms incorporate Support Vector Machine (SVM), Random Forest (RF), Convolutional Neural Network (CNN), and MobileNet with accuracy rates between 64.3 and 100%. …”
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520
Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma
Published 2019“…<h3>Background</h3><p dir="ltr">Predictive modeling with longitudinal electronic health record (EHR) data offers great promise for accelerating personalized medicine and better informs clinical decision-making. …”