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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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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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A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network
Published 2019“…In order to address this issue, in this paper, we propose a novel hybrid approach with both convolutional and recurrent neural networks combined, which is based on the long short-term memory module. Featuring the capability of learning the correlations of time-series data, the proposed deep learning method is well-suited for extracting the valuable transient feature contained in the very beginning of the response curve. …”
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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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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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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. …”
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Hybrid deep learning based threat intelligence framework for Industrial IoT systems
Published 2025“…The proposed approach was also compared against several contemporary deep learning-based architectures and existing benchmark algorithms. …”
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Developing a UAE-Based Disputes Prediction Model using Machine Learning
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Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT
Published 2021“…This paper proposes an Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT. …”
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Machine learning approach for the classification of corn seed using hybrid features
Published 2020“…The nine optimized features have been acquired by employing the correlation-based feature selection (CFS) technique with the Best First search algorithm. …”
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Stability improvement of the PSS-connected power system network with ensemble machine learning tool
Published 2022“…The backtracking search algorithm (BSA) based proposed ensemble model is formed by combining three machine learning (ML) techniques, namely the extreme learning machine (ELM), neurogenetic (NG) system, and multi-gene genetic programming (MGGP). …”
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Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark
Published 2021“…The optimal value of clustering is used in this paper to cluster the data into groups to be able to reduce the computational time additionally. Multiple tree-based machine learning algorithms are tested with parallel computation to evaluate the performance with tunable parameters on a real-world dataset. …”
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A Comprehensive Overview of the COVID-19 Literature: Machine Learning–Based Bibliometric Analysis
Published 2021“…Specifically, we used a clustering algorithm to group published articles based on the similarity of their abstracts to identify research hotspots and current research directions. …”