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learning algorithm » learning algorithms (Expand Search)
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learning algorithm » learning algorithms (Expand Search)
mean algorithm » deer algorithm (Expand Search), search algorithm (Expand Search)
code algorithm » cosine algorithm (Expand Search), rd algorithm (Expand Search), colony algorithm (Expand Search)
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FPGA-Based Network Traffic Classification Using Machine Learning
Published 2020“…Classification approaches based on machine learning techniques have shown promising results with high levels of accuracy. …”
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FPGA-Based Network Traffic Classification Using Machine Learning
Published 2019Get full text
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Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine
Published 2024“…Lastly, a newly improved learning algorithm encompasses a modified pelican optimization algorithm (MOD-POA) and an extreme learning machine (ELM) for classification tasks. …”
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Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory
Published 2025Subjects: -
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Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars
Published 2023“…Finally, a design equation that can predict the shear capacity of one-way BFRC-BFRP slabs was proposed based on genetic algorithm. The proposed model showed the best prediction accuracy compared to the available design codes and guidelines with a mean of predicted to experimental shear capacities (V<sub>pred</sub>/V<sub>exp</sub>) ratio of 0.97 and a coefficient of variation of 17.91%.…”
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PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT
Published 2023“…The tweets are classified into categories based on the feeling: Positive and negative. The authors applied Machine Learning algorithms, Support Vector Machines (SVM) and the Naïve Bayes (NB) and accordingly they compared the accuracy between them. …”
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PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT
Published 2023“…The tweets are classified into categories based on the feeling: Positive and negative. The authors applied Machine Learning algorithms, Support Vector Machines (SVM) and the Naïve Bayes (NB) and accordingly they compared the accuracy between them. …”
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Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm
Published 2022“…Grasshopper optimization algorithm (GOA) is a fresh population based meta-heuristic algorithm that mimics the swarming behavior of grasshoppers in nature, which has good convergence ability towards optima. …”
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Predicting Plasma Vitamin C Using Machine Learning
Published 2022“…The objective of this study is to predict plasma vitamin C using machine learning. The NHANES dataset was used to predict plasma vitamin C in a cohort of 2952 American adults using regression algorithms and clustering in a way that a hypothetical health application might. …”
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The Use of Microwave Tomography in Bone Healing Monitoring
Published 2019Get full text
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Bird’s Eye View feature selection for high-dimensional data
Published 2023“…BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
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MSLP: mRNA subcellular localization predictor based on machine learning techniques
Published 2023“…We propose a novel combination of four types of features representing k-mer, pseudo k-tuple nucleotide composition (PseKNC), physicochemical properties of nucleotides, and 3D representation of sequences based on Z-curve transformation to feed into machine learning algorithm to predict the subcellular localization of mRNAs.…”
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Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators
Published 2021“…The outcomes of the DNA microarray is a table/matrix, called gene expression data. Pattern recognition algorithms are widely applied to gene expression data to differentiate between health and cancerous patient samples. …”
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Behavior-Based Machine Learning Approaches to Identify State-Sponsored Trolls on Twitter
Published 2020“…We have proposed a set of behavioral features of users' activities on Twitter. Based on these features, we developed four classification models to identify political troll accounts, these models are based on decision tree, random forest, Adaboost, and gradient boost algorithms. …”