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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks
Published 2025“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …”
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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing
Published 2016“…A Master of Science thesis in Engineering Systems Management by Alia Al Sadawi entitled, "Efficient Dynamic Cost Scheduling Algorithm for Data Batch Process," submitted in May 2016. …”
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doctoralThesis -
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Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain
Published 2021“…An iterative dynamic scheduling algorithm (DCSDBP) was developed to address the data batching process. …”
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Genetic and heuristic algorithms for regrouping service sites. (c2000)
Published 2000Subjects: “…Genetic algorithms -- Data processing…”
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masterThesis -
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On the steiner walk problem. (c2009)
Published 2009Subjects: “…Euclidean algorithm -- Data processing…”
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A genetic algorithm for corrective retesting. (c1995)
Published 1995Subjects: Get full text
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masterThesis -
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DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data
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Three-phase approach for curriculum-based course timetabling problem. (c2012)
Published 2012Subjects: “…Scheduling -- Data processing…”
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Clustering/partitioning algorithms and comparative analysis
Published 1989Subjects: Get full text
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Improved search-tree algorithms for the cluster edit problem. (c2011)
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masterThesis -
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A Survey of Data Clustering Techniques
Published 2023Subjects: “…Cluster analysis -- Data processing…”
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A decentralized load balancing strategy for parallel search-three optimization. (c2010)
Published 2010Subjects: “…Trees (Graph theory) -- Data processing…”
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A parallel search tree algorithm for vertex cover on graphical processing units. (c2013)
Published 2013Subjects: “…Trees (Graph theory) -- Data processing…”
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masterThesis -
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Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval
Published 2024“…<p dir="ltr">Fault detection and diagnosis (FDD) systems play a crucial role in maintaining the adequate execution of the monitored process. One of the widely used data-driven FDD methods is the Principal Component Analysis (PCA). …”