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robust algorithm » mould algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
develop » developed (Expand Search)
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Concurrent BIST Synthesis and Test Scheduling Using Genetic Algorithms
Published 2007“…This paper presents an efficient method for concurrent built-in self-test synthesis and test scheduling in high-level synthesis. …”
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Variable Selection in Data Analysis: A Synthetic Data Toolkit
Published 2024“…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …”
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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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Auto-indexing Arabic texts based on association rule data mining. (c2015)
Published 2015“…Our model denotes extracting new relevant words by relating those chosen by the previous classical methods, to new words using data mining rules. …”
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Estimating Construction Project Duration Using a Machine Learning Algorithm
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Four quadrant robust quick response optimally efficient inverterfed induction motor drive
Published 1989“…The control algorithms developed are readily implementable with present-day microprocessors…”
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Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment
Published 2023“…The artificial neural network demonstrates a higher prediction accuracy and is used as the system model in the proposed control framework. A robust model predictive control strategy, based on the minimax objective function and particle swarm optimisation algorithm, is developed to handle the uncertainties in the system. …”
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An Event-Triggered Robust Attitude Control of Flexible Spacecraft With Modified Rodrigues Parameters Under Limited Communication
Published 2019“…Aligned with these design objectives, a robust event-triggered attitude control algorithm is proposed to regulate the orientation of a flexible spacecraft subjected to parametric uncertainties, external disturbances, and vibrations due to flexible appendages. …”
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Optimizing Document Classification: Unleashing the Power of Genetic Algorithms
Published 2023“…Additionally, our proposed model optimizes the features using a genetic algorithm. Optimal feature selection performances a crucial role in this domain, enhancing the overall accuracy of the document classification system while reducing the time complexity associated with selecting the most relevant features from this large-dimensional space. …”
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Mining airline data for CRM strategies. (c2006)
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Indexing Arabic texts using association rule data mining
Published 2019“…The model denotes extracting new relevant words by relating those chosen by previous classical methods to new words using data mining rules. …”
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Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems
Published 2022“…Data-driven algorithms with capabilities to predict the system’s dynamic behavior still need to be developed. …”
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Artificial intelligence-based methods for fusion of electronic health records and imaging data
Published 2022“…In our analysis, a typical workflow was observed: feeding raw data, fusing different data modalities by applying conventional machine learning (ML) or deep learning (DL) algorithms, and finally, evaluating the multimodal fusion through clinical outcome predictions. …”
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A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai
Published 2024“…Data-driven decision-making has become increasingly widespread and relevant across all business areas, including private and public sectors. …”
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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks
Published 2025“…Ensemble schemes such as Gaussian process regression with simple averaging and gradient boosting regressors fortified by permutation feature importance improve robustness in noisy or multi-alloy environments. 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. …”