Search Results - (( parameter education learning algorithm ) OR ( parameter mitigation clustering algorithm ))
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Enhancement Of Clustering Algorithm Using 3D Euclidean Distance To Improve Network Connectivity In Wireless Sensor Networks For Correlated Node Behaviours
Published 2024“…Thus, this research proposes enhancement on clustering algorithm to mitigate the impact of correlated node behaviour on network performances. …”
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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Optimization of balanced academic curriculum problem in educational institutions using teaching learning based optimization algorithm
Published 2025“…Future research could focus on enhancing TLBO through hybridization with other algorithms and applying it to real-world BACP scenarios in educational institutions.…”
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Rao-SVM machine learning algorithm for intrusion detection system
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A coalition model for efficient indexing in wireless sensor network with random mobility / Hazem Jihad Ali Badarneh
Published 2021“…The proposed framework aims to improve the indexing packets and mitigate the disseminated data. Static-Coalition algorithm rearranges the packets in each gateway, by source (location attribute). …”
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Enhancing hyperparameters of LSTM network models through genetic algorithm for virtual learning environment prediction
Published 2025“…These findings highlight the effectiveness of adaptive and genetic algorithms in enhancing LSTM model performance for VLE prediction, offering valuable insights for educational technology advancement.…”
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Detection And Identification Of Stiction In Control Valves Based On Fuzzy Clustering Method
Published 2016“…This modification prevents the fuzzy clustering algorithm from turning into numerical problem. …”
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RAED: Response Analysis of Educational Data for leveraging knowledge dissemination system
Published 2015“…The proposed architecture provides future researchers to validate their algorithm and get the provisioned output for the teaching-learning added for intelligent applications Keywords; Educational Data, Big Data, Data Analytics, Data Mining, Knowledge Discovery…”
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Proceeding Paper -
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Machine learning for mapping and forecasting poverty in North Sumatera: a datadriven approach
Published 2024“…Poverty mapping and prediction were conducted in North Sumatra to get a precise spatial distribution of poverty, the operation of the poverty model, and forecasting using machine learning (ML). Poverty prediction was conducted using a random forest (RF) algorithm and poverty mapping was conducted using the K-Means algorithm. …”
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RAED: Response analysis of educational data for leveraging knowledge dissemination system
Published 2015“…The proposed architecture provides future researchers to validate their algorithm and get the provisioned output for the teaching-learning added for intelligent applications…”
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Proceeding Paper -
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Model-based hybrid variational level set method applied to object detection in grey scale images
Published 2024“…To tackle the persistent challenge of segmenting grayscale images with both uneven characteristics and high noise levels, a hybrid level-set algorithm based on kernel metrics is introduced. This algorithm leverages an improved multi-scale mean filter to mitigate grayscale inhomogeneity while reducing the impact of scale parameter selection. …”
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Smart waste management system with IoT monitoring
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Cognitive knowledge-based model for adaptive feedback: A case in physics / Andrew Thomas Bimba
Published 2019“…Tailoring feedback according to student’s characteristics and other external parameters is a promising way to implement adaptation in computer-based learning environment. …”
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Predicting noise-induced hearing loss (NIHL) in TNB workers using GDAM algorithm
Published 2012“…This research proposed an algorithm for improving the current working performance of Back-propagation algorithm by adaptively changing the momentum value and at the same time keeping the ‘gain’ parameter fixed for all nodes in the neural network. …”
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