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modeling algorithm » scheduling algorithm (Expand Search)
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modeling algorithm » scheduling algorithm (Expand Search)
dbscan clustering » data clustering (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
element » elements (Expand Search)
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A Survey of Data Clustering Techniques
Published 2023“…This survey examines seven widely recognized clustering techniques, namely k-means, G-means, DBSCAN, Agglomerative hierarchical clustering, Two-stage density (DBSCAN and k-means) algorithm, Two-levels (DBSCAN and hierarchical) clustering algorithm, and Two-stage MeanShift and K-means clustering algorithm and compares them over a real dataset - The Blockchain dataset, including prominent cryptocurrencies like Binance, Bitcoin, Doge, and Ethereum, under several metrics such as silhouette coefficient, Calinski-Harabasz, Davies-Bouldin Index, time complexity, and entropy.…”
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Bird’s Eye View feature selection for high-dimensional data
Published 2023“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. 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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Scatter search for protein structure prediction. (c2008)
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masterThesis -
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Evolutionary algorithm for protein structure prediction
Published 2010“…In this paper, we present an improved genetic algorithm (GA) for predicting 3D structures of proteins based on the hydrophobic polar model. …”
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XBeGene: Scalable XML Documents Generator by Example Based on Real Data
Published 2012“…Inspired by the query-by-example paradigm in information retrieval, Our generator system i)allows the user to provide her own sample XML documents as input, ii) analyzes the structure, occurrence frequencies, and content distributions for each XML element in the user input documents, and iii) produces synthetic XML documents which closely concur, in both structural and content features, to the user's input data. …”
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A flexible genetic algorithm-fuzzy regression approach for forecasting: The case of bitumen consumption
Published 2019“…This study aims to introduce a flexible genetic algorithm-fuzzy regression approach for forecasting the future bitumen consumption. …”
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A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai
Published 2024“…The proposed framework comprises key elements: Important Decisions derived from interviews with transportation leaders, Knowledge Management enhanced by AI algorithms, Data Mining/Analysis utilizing historical data, the Fleet Management System employing Oracle ERP, and a Data-Driven Decision Support Framework that leans towards the extended framework approach. …”
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Brain Source Localization in the Presence of Leadfield Perturbations
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doctoralThesis -
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Protein structure prediction in the 3D HP model
Published 2009“…In this paper, we present a Particle Swarm Optimization (PSO) based algorithm for predicting protein structures in the 3D HP model. …”
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Nonlinear analysis of shell structures using image processing and machine learning
Published 2023“…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”
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Particle swarm optimization approach for protein structure prediction in the 3D HP model
Published 2012“…In this paper, we present a particle swarm optimization (PSO) based algorithm for predicting protein structures in the 3D hydrophobic polar model. …”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI
Published 2025“…The RF model achieved up to 99% balanced accuracy on the adult dataset, with similarly strong performance on the children and adolescent datasets using five-fold cross-validation (CV). …”
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Development of Machine Learning Models for Studying the Premixed Turbulent Combustion of Gas-To-Liquids (GTL) Fuel Blends
Published 2024“…The k-fold cross-validation technique is used for model training, and the developed neural network-based model is used to investigate the effects of operating parameters on the premixed turbulent flames. …”