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modeling algorithm » scheduling algorithm (Expand Search)
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elemental » elementary (Expand Search), elements (Expand Search), element (Expand Search)
modeling algorithm » scheduling algorithm (Expand Search)
code algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search)
rd algorithm » _ algorithms (Expand Search)
elemental » elementary (Expand Search), elements (Expand Search), element (Expand Search)
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Data Embedding in HEVC Video by Modifying the Partitioning of Coding Units
Published 2019Subjects: Get full text
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Improved scatter search algorithm for predicting all-atoms protein structures using charmm22 energy model. (c2010)
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masterThesis -
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Scatter search for protein structure prediction. (c2008)
Published 2008Subjects: Get full text
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masterThesis -
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Development of an Optimization Algorithm for Internet Data Traffic
Published 2020“…The algorithm monitors data repetitions in IP datagram and prepares a compression code in response of this repetition. …”
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Practical single node failure recovery using fractional repetition codes in data centers
Published 2016“…FR codes consist of a concatenation of an outer maximum distance separable (MDS) code and an inner fractional repetition code that splits the data into several blocks and stores multiple replicas of each on different nodes in the system. …”
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Using genetic algorithms to optimize software quality estimation models
Published 2004“…Most such models are constructed using statistical or machine learning techniques. …”
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masterThesis -
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024“…UniBFS exploits the inherent characteristic of binary algorithms-binary coding-to search the entire problem space for identifying relevant features while avoiding irrelevant ones. …”
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Detection of statistically significant network changes in complex biological networks
Published 2017“…</p><h3>Methods</h3><p dir="ltr">In this paper, we propose an improvement over the state-of-the-art based on the Generalized Hamming Distance adopted for evaluating the topological difference between two networks and estimating its statistical significance. The proposed procedure exploits a more effective model selection criteria to generate <i>p</i>-values for statistical significance and is more efficient in terms of computational time and prediction accuracy than literature methods. …”
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A hybrid heuristic approach to optimize rule based software quality estimation models. (c2008)
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masterThesis -
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Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory
Published 2025Subjects: -
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A decentralized load balancing strategy for parallel search-three optimization. (c2010)
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Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy
Published 2023“…This study investigates the gradient-based, evolutionary, and Bayesian-based optimization algorithms. Combining statistical and ranking analyses confirms that the Levenberg–Marquardt (LM) is the most efficient optimization technique for training the MLPNN model. …”
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Oversampling techniques for imbalanced data in regression
Published 2024“…For such high-dimension data our approach outperforms the Synthetic Minority Oversampling Technique for Regression (SMOTER) algorithm for the IMDB-WIKI and AgeDB image datasets. …”