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coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
using algorithm » cosine algorithm (Expand Search)
forest using » faces using (Expand Search), notes using (Expand Search)
element » elements (Expand Search)
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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 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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Automatic Video Summarization Using HEVC and CNN Features
Published 2022Get full text
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Habitat in flames: How climate change will affect fire risk across koala forests
Published 2023“…</p><p><br></p><h3>Method:</h3><p dir="ltr">The Decision Tree machine learning algorithm was applied to generate a fire susceptibility index (a measure of the potential for a given area or region to experience wildfires) using a dataset of conditioning factors, namely: altitude, aspect, rainfall, distance from rivers, distance from roads, forest type, geology, koala presence and future dietary sources, land use-land cover (LULC), normalized difference vegetation index (NDVI), slope, soil, temperature, and wind speed.…”
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A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition
Published 2025“…Random Forest (RF) is simpler and more efficient than other ML algorithms. …”
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Spatiotemporal Mapping and Monitoring of Mangrove Forests Changes From 1990 to 2019 in the Northern Emirates, UAE Using Random Forest, Kernel Logistic Regression and Naive Bayes Tr...
Published 2020“…The approach was developed based on random forest (RF), Kernel logistic regression (KLR), and Naive Bayes Tree machine learning algorithms which use multitemporal Landsat images. …”
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Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology
Published 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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CNN and HEVC Video Coding Features for Static Video Summarization
Published 2022“…Combining the proposed solution with Multi-CNN features and using a random forest classifier, it was shown that the proposed solution achieved an average F-score of 0.98.…”
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Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network
Published 2024“…These algorithms include random forest (RF) classification and artificial neural networks (ANN). …”
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A Parallel Neural Networks Algorithm for the Clique Partitioning Problem
Published 2002“…The proposed algorithm has a time complexity of O(1) for a neural network with n vertices and c cliques. …”
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A FUZZY EVOLUTIONARY ALGORITHM FOR TOPOLOGY DESIGN OF CAMPUS NETWORKS
Published 2020“…In this paper, we present a Simulated Evolution algorithm for the design of campus network topology. …”
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FPGA-Based Network Traffic Classification Using Machine Learning
Published 2020“…In this paper, the suitability of packet-level and flow-level features is validated using stepwise regression and random forest feature selection. …”
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A Novel Big Data Classification Technique for Healthcare Application Using Support Vector Machine, Random Forest and J48
Published 2022“…The performance of the algorithms for accuracy was evaluated using the Healthcare (heart attack possibility) dataset, freely available on kagle. …”
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FPGA-Based Network Traffic Classification Using Machine Learning
Published 2019Get full text
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Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm
Published 2020“…The problem consists of deciding the number, types, and locations of the network active elements (hubs, switches, and routers), as well as the links and their capacities. …”
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Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm
Published 2020“…The problem consists of deciding the number, types, and locations of the network active elements (hubs, switches, and routers), as well as the links and their capacities. …”
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Nonlinear analysis of shell structures using image processing and machine learning
Published 2023“…We show that the results of the trained network agree well with the results of the nonlinear finite element analysis. …”
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