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hiding algorithm » scheduling algorithm (Expand Search), cosine algorithm (Expand Search)
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data hiding » data mining (Expand Search)
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Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm
Published 2022“…Researchers have scrutinized data hiding schemes in recent years. Data hiding in standard images works well, but does not provide satisfactory results in distortion-sensitive medical, military, or forensic images. …”
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
Published 2016Subjects: Get full text
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A reduced model for phase-change problems with radiation using simplified PN approximations
Published 2025“…The integro-differential equation for the full radiative transfer is replaced by a set of differential equations which are independent of the angle variable and easy to solve using conventional computational methods. To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. …”
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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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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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Valuation of commodity option prices under a regime-switching model with stochastic convenience yield: Model calibration using flower pollination optimization algorithm
Published 2025Subjects: “…Expectation–maximization algorithm…”
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New fault models and efficient BIST algorithms for dual-portmemories
Published 1997“…These modifications allow multiple access of memory cells for increased test speed with minimal overhead on both silicon area and device performance. New fault models are proposed, and efficient O(n) test algorithms are described for both the memory array and the address decoders. …”
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Parameter Estimation Of Wiener-Hammerstein Models Via Genetic Algorithms
Published 2020“…Also, the algorithm is applied to model a DC generator with some nonlinear characteristics…”
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Automating UML Models Refactoring using Search-Based Algorithms
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A genetic-based algorithm for fuzzy unit commitment model
Published 2000“…The genetic algorithm (GA) approach is then used to solve the proposed fuzzy UCP model. …”
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Using genetic algorithms to optimize software quality estimation models
Published 2004“…This thesis explores the use of genetic algorithms for the problem of optimizing existing rule-based software quality estimation models. …”
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Combining and adapting software quality predictive models by genetic algorithms
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Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification
Published 2025Subjects: “…Adagrad optimization algorithm…”
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Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications
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Brain Source Localization in the Presence of Leadfield Perturbations
Published 2015Get full text
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Nonlinear model predictive control of Hammerstein and Wiener modelsusing genetic algorithms
Published 2001“…In this paper a novel approach for the implementation of nonlinear MPC is proposed using genetic algorithms (GAs). The proposed method formulates the MPC as an optimization problem and genetic algorithms are used in the optimization process. …”
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An ant colony optimization algorithm to improve software quality prediction models
Published 2011“…Results Results show that our approach out-performs the machine learning algorithm C4.5 as well as random guessing. It also preserves the expressiveness of the models which provide not only the classification label but also guidelines to attain it. …”
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