Search alternatives:
case scheduling » task scheduling (Expand Search), ahead scheduling (Expand Search)
using algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
pooled using » problem using (Expand Search), tool using (Expand Search), tools using (Expand Search)
case scheduling » task scheduling (Expand Search), ahead scheduling (Expand Search)
using algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
pooled using » problem using (Expand Search), tool using (Expand Search), tools using (Expand Search)
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1
The buffered work-pool approach for search-tree based optimization algorithms
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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing
Published 2016Get full text
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Power-constrained system-on-a-chip test scheduling using a genetic algorithm
Published 2006“…This paper presents an efficient approach for the test scheduling problem of core-based systems based on a genetic algorithm. …”
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5
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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Optimized Load-Scheduling Algorithm for CubeSat's Electric Power System Management Considering Communication Link
Published 2023“…The solution obtained shows that the proposed scheduling algorithm meets the communication system's requirements while conserving power and energy resources.…”
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Efficient Prioritization and Processor Selection Schemes for HEFT Algorithm: A Makespan Optimizer for Task Scheduling in Cloud Environment
Published 2022“…Among these methods, the Heterogeneous Earliest Finish Time (HEFT) algorithm is recognized to produce optimal outcomes in a shorter time period for scheduling tasks in a heterogeneous environment. …”
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MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network
Published 2022“…Because the diagnosis of many neurological diseases is heavily reliant on clean EEG data, it is critical to eliminate motion artifacts from motion-corrupted EEG signals using reliable and robust algorithms. Although a few deep learning-based models have been proposed for the removal of ocular, muscle, and cardiac artifacts from EEG data to the best of our knowledge, there is no attempt has been made in removing motion artifacts from motion-corrupted EEG signals: In this paper, a novel 1D convolutional neural network (CNN) called multi-layer multi-resolution spatially pooled (MLMRS) network for signal reconstruction is proposed for EEG motion artifact removal. …”
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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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12
Optimal Management of Mobile Energy Generation and Storage Systems
Published 2018Get full text
doctoralThesis -
13
Estimating Construction Project Duration Using a Machine Learning Algorithm
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masterThesis -
14
Incremental Genetic Algorithm
Published 2006“…Classical Genetic Algorithms (CGA) are known to find good sub-optimal solutions for complex and intractable optimization problems. …”
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An efficient method for the open-shop scheduling problem using simulated annealing
Published 2016“…This paper presents a simulated annealing algorithm in order to solve the nonpreemptive open-shop scheduling problem with the objective of minimizing the makespan. …”
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A GRASP Approach for Solving Large-Scale Electric Bus Scheduling Problems
Published 2021“…The GRASP algorithm is used for case studies on several public transport systems having various properties and sizes. …”
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Incremental & classical genetic algorithm. (c2001)
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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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masterThesis -
20
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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