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modeling algorithm » scheduling algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
maya algorithm » jaya algorithm (Expand Search)
level modeling » event modeling (Expand Search)
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Scheduling and allocation in high-level synthesis using stochastic techniques
Published 2020“…High-level synthesis is the process of automatically translating abstract behavioral models of digital systems to implementable hardware. …”
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Decision-level Gait Fusion for Human Identification at a Distance
Published 2014Get full text
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Formal synthesis of VLSI layouts from algorithmic specifications
Published 2020“…In this paper we present a formal approach for high level synthesis. This formal high level syntesis system uses recursive algorithms to model the behaviour to be synthesized. …”
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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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A neural networks algorithm for data path synthesis
Published 2003“…This paper presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …”
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Spectrum Sensing Algorithms for Cooperative Cognitive Radio Networks
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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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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing
Published 2016Get full text
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Impact of Charging Electric Vehicles under Different State of Charge Levels and Extreme Conditions
Published 2021“…This paper defines extreme conditions as the state of a load or network that breaks the limits of the constraints in an optimization model. Once these constraints are violated, the optimization algorithm might not work correctly and might not converge to a feasible solution, especially when the complexity of the system increases and includes nonlinearities. …”
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Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain
Published 2021“…The objective is to minimize different cost types while satisfying constraints such as resources availability, customer service level, and tasks dependency relation. The algorithm proved its effectiveness by allocating tasks with higher priority and weight while taking into consideration customers’ Service Level Agreement, time, and different types of costs, which led to a lower total cost of the batching process. …”
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Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction
Published 2025“…This adjustment highlights the importance of concentration levels in reflecting the variability specific to individual interaction sites. …”
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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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Genetic Algorithm for Solving Site Layout Problem with Unequal-Size and Constrained Facilities
Published 2002“…The paper concludes with examples illustrating the strength and limitations of the proposed algorithm in the cases of ~1! loosely versus tightly constrained layouts with equal levels of interaction between facilities; ~2! …”
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Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition
Published 2021“…<p>Different aggregation levels of the electric grid's big data can be helpful to develop highly accurate deep learning models for Short-term Load Forecasting (STLF) in electrical networks. …”
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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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Multi-Model Investigation and Adaptive Estimation of the Acoustic Release of a Model Drug From Liposomes
Published 2019“…The best-fitting mathematical model is then enhanced using a Kalman filtering (KF) algorithm to account for the statistics of the dynamic and measurements noise sequences in predicted drug release. …”
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A Parallel Genetic Algorithm for the Geometrically Constrained Site Layout Problem with Unequal-Size Facilities
Published 2010“…Parallel genetic algorithms techniques have been used in a variety of computer engineering and science areas. …”
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