Showing 1 - 20 results of 52 for search '(((( elements custom algorithm ) OR ( element data algorithm ))) OR ( path modeling algorithm ))', query time: 0.13s Refine Results
  1. 1

    A neural networks algorithm for data path synthesis by Harmanani, Haidar M.

    Published 2003
    “…This paper presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …”
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    Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

    Published 2023
    “…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. 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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    A method for data path synthesis using neural networks by Harmanani, H.

    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 by M. Ghoniem , Rania

    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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    A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)

    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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    XBeGene: Scalable XML Documents Generator by Example Based on Real Data by Harazaki, Manami

    Published 2012
    “…Inspired by the query-by-example paradigm in information retrieval, Our generator system i)allows the user to provide her own sample XML documents as input, ii) analyzes the structure, occurrence frequencies, and content distributions for each XML element in the user input documents, and iii) produces synthetic XML documents which closely concur, in both structural and content features, to the user's input data. …”
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    Hybrid Optimized Approaches for Routing and Resource Reservation Protocols in Optical Networks by Akhtar Nawaz Khan (16888734)

    Published 2021
    “…Route-Model computes routing information which is integrated with the first-fit algorithm. …”
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    A systolic algorithm for VLSI design of a 1/N rate Viterbi decoder by Sait, Sadiq M.

    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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    A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai by ALGHANEM, HANI SUBHI MOHD

    Published 2024
    “…The proposed framework comprises key elements: Important Decisions derived from interviews with transportation leaders, Knowledge Management enhanced by AI algorithms, Data Mining/Analysis utilizing historical data, the Fleet Management System employing Oracle ERP, and a Data-Driven Decision Support Framework that leans towards the extended framework approach. …”
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    Nonlinear analysis of shell structures using image processing and machine learning by M.S. Nashed (16392961)

    Published 2023
    “…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”
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