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modeling algorithm » scheduling algorithm (Expand Search)
learner algorithm » learning algorithms (Expand Search), search algorithm (Expand Search), deer algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
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Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS
Published 2018“…We then provide a general keyword query model with specially tailored query processing algorithms built on top of SemIndex, in order to produce semantic-aware results, allowing the user to choose the results' semantic coverage and expressiveness based on her needs. …”
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Bird’s Eye View feature selection for high-dimensional data
Published 2023“…BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
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Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying
Published 2023“…Most methods rely on the concept of Lowest Comment Ancestor (LCA) between two or multiple structural nodes to identify the most specific XML elements containing query keywords posted by the user. Yet, few of the existing approaches consider XML semantics, and the methods that process semantics generally rely on computationally expensive word sense disambiguation (WSD) techniques, or apply semantic analysis in one stage only: performing query relaxation/refinement over the bag of words retrieval model, to reduce processing time. …”
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Particle swarm optimization algorithm: review and applications
Published 2024“…Particle swarm optimization (PSO) is a heuristic global optimization technique and an optimization algorithm that is swarm intelligence-based. It is based on studies into the movement of bird flocks. …”
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RHEEMix in the data jungle: a cost-based optimizer for cross-platform systems.
Published 2020“…Our main contributions are: (i) a mechanism based on graph transformations to explore alternative execution strategies; (ii) a novel graph-based approach to determine efficient data movement plans among subtasks and platforms; and (iii) an efficient plan enumeration algorithm, based on a novel enumeration algebra. …”
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Towards Scalable Process Mining Pipelines
Published 2023“…Contributions have covered the spectrum of better algorithms, richer comparison metrics, and movement towards online analysis for process data. …”
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SemIndex+: A semantic indexing scheme for structured, unstructured, and partly structured data
Published 2018“…We provide a general keyword query model allowing the user to choose the results’ semantic coverage and expressiveness based on her needs. …”
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Real-Time Path-Planning using Depth/INS Sensor Fusion for Localization
Published 2019Get full text
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Design of A Theoretical Framework For A Real-Time Fire Evacuation Guidance System
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Solar power forecasting beneath diverse weather conditions using GD and LM-artificial neural networks
Published 2023“…A case study has been done in the Peer Panjal region. The data collected for four months with various parameters have been applied randomly as input data using GD and LM type of artificial neural network compared to actual solar energy data. …”
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Automated skills assessment in open surgery: A scoping review
Published 2025“…The assessment input for the automation algorithms were predominantly hand movement. Around 37.5 % (<i>n </i>= 15) of the studies assessed algorithm performance using classification accuracy. …”
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SemIndex: Semantic-Aware Inverted Index
Published 2017“…We also provide an extended query model and related processing algorithms with the help of SemIndex. …”
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Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series
Published 2013Get full text
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Identity and Aggregate Signature-Based Authentication Protocol for IoD Deployment Military Drone
Published 2021“…This risk is specifically eminent in monitoring data transmission traffic, espionage, troop movement, border surveillance, searching, and warfare battlefield phenomenon, etc. …”
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Modelling Exchange Rates during Currency Crisis using Neural Networks
Published 2006“…The models are built using the feedforward ANN structure trained by the backpropagation algorithm. Exchange rate data from the Lebanese currency crisis period of 1985-1992 is used for training, testing and evaluation of the models. …”
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Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study
Published 2024“…Furthermore, future studies could evaluate more efficient modeling algorithms, especially those combining topic modeling with statistical uncertainty quantification, such as conformal prediction.…”
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