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modeling algorithm » scheduling algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (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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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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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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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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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. …”
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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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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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Hybrid Optimized Approaches for Routing and Resource Reservation Protocols in Optical Networks
Published 2021“…Route-Model computes routing information which is integrated with the first-fit algorithm. …”
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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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A systolic algorithm for VLSI design of a 1/N rate Viterbi decoder
Published 1989“…The second consists of a matrix of simpler processors which update survived paths and provide the decoded output. The systolic algorithm is modeled in AHPL to verify functional correctness. …”
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Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators
Published 2021“…The outcomes of the DNA microarray is a table/matrix, called gene expression data. Pattern recognition algorithms are widely applied to gene expression data to differentiate between health and cancerous patient samples. …”
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