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modeling algorithm » scheduling algorithm (Expand Search)
code algorithm » cosine algorithm (Expand Search), rd algorithm (Expand Search), colony algorithm (Expand Search)
a modeling » _ modeling (Expand Search)
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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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A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models
Published 2010“…In this work, we present a genetic algorithm to optimize predictive models used to estimate software quality characteristics. …”
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Large language models for code completion: A systematic literature review
Published 2024“…Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. While several research papers have focused on the use of LLMs for code completion, these studies are fragmented, and there is no systematic overview of the use of LLMs for code completion. …”
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024“…<p>Feature selection (FS) is a crucial technique in machine learning and data mining, serving a variety of purposes such as simplifying model construction, facilitating knowledge discovery, improving computational efficiency, and reducing memory consumption. …”
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Data Embedding in HEVC Video by Modifying the Partitioning of Coding Units
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Accurate multiple network alignment through context-sensitive random walk
Published 2015“…In this work, we propose a novel multiple network alignment algorithm based on a context-sensitive random walk model. …”
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A New Parallel Genetic Algorithm Model
Published 2020“…This paper presents an implementation of three Genetic Algorithm models for solving a reliability optimization problem for a redundancy system with several failure modes, a modification on a parallel a genetic algorithm model and a new parallel genetic algorithm model. …”
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Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory
Published 2025Subjects: -
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New fault models and efficient BIST algorithms for dual-portmemories
Published 1997“…The testability problem of dual-port memories is investigated. A functional model is defined, and architectural modifications to enhance the testability of such chips are described. …”
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A genetic-based algorithm for fuzzy unit commitment model
Published 2000“…This paper presents a fuzzy model for the unit commitment problem (UCP). …”
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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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Valuation of commodity option prices under a regime-switching model with stochastic convenience yield: Model calibration using flower pollination optimization algorithm
Published 2025“…<p>This research work seeks to construct a model for commodity spot prices by incorporating the concept of stochastic convenience yield within a Markov-switching framework. …”
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A Novel Hybrid Genetic-Whale Optimization Model for Ontology Learning from Arabic Text
Published 2019“…The previously published research on Arabic ontology learning from text falls into three categories: developing manually hand-crafted rules, using ordinary supervised/unsupervised machine learning algorithms, or a hybrid of these two approaches. The model proposed in this work contributes to Arabic ontology learning in two ways. …”
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A hybrid heuristic approach to optimize rule based software quality estimation models. (c2008)
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Modeling and Control of a Robot Based Rehabilitation System for the Head-Neck Joint
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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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