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modeling algorithm » scheduling algorithm (Expand Search)
method algorithm » mould algorithm (Expand Search)
path modeling » spatial modeling (Expand Search)
element » elements (Expand Search)
relating » regulating (Expand Search), relations (Expand Search), relative (Expand Search)
modeling algorithm » scheduling algorithm (Expand Search)
method algorithm » mould algorithm (Expand Search)
path modeling » spatial modeling (Expand Search)
element » elements (Expand Search)
relating » regulating (Expand Search), relations (Expand Search), relative (Expand Search)
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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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Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain
Published 2021“…An iterative dynamic scheduling algorithm (DCSDBP) was developed to address the data batching process. …”
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Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence
Published 2020“…For the future improvements can be done to this work by integrating other related data such as social media news using sentimental analysis. …”
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Mining airline data for CRM strategies. (c2006)
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A Survey of Data Clustering Techniques
Published 2023“…Clustering, an unsupervised learning technique, aims to identify a specific number of clusters to effectively categorize the data through data grouping. Hence, clustering is related to many fields and is used in various applications that deal with large datasets. …”
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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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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
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Brain Source Localization in the Presence of Leadfield Perturbations
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A method for data path synthesis using neural networks
Published 2017“…Presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …”
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A Novel Hybrid Genetic-Whale Optimization Model for Ontology Learning from Arabic Text
Published 2019“…The previously published research on Arabic ontology learning from text falls into three categories: developing manually hand-crafted rules, using ordinary supervised/unsupervised machine learning algorithms, or a hybrid of these two approaches. The model proposed in this work contributes to Arabic ontology learning in two ways. …”
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Monitoring Bone Density Using Microwave Tomography of Human Legs: A Numerical Feasibility Study
Published 2021“…This study was performed using an in-house finite-element method contrast source inversion algorithm (FEM-CSI). …”
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Auto-indexing Arabic texts based on association rule data mining. (c2015)
Published 2015“…The model uses the Apriori Algorithm - an association rule algorithm for extracting frequent sets containing related items - to extract relations between words in the texts to be indexed with words from texts that belong to the same category. …”
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A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network
Published 2019“…Moreover, various standard drift related experiments are conducted, of which the results validate our proposed algorithm's superior robustness for the wide range of real-life applications.…”
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Estimating Construction Project Duration Using a Machine Learning Algorithm
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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT
Published 2023“…<p dir="ltr">In mobile edge computing (MEC), it is difficult to recognise an optimum solution that can perform in limited energy by selecting the best communication path and components. This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …”