Showing 1 - 20 results of 44 for search '(( element network algorithm ) OR ((( element mining algorithm ) OR ( level coding algorithm ))))', query time: 0.14s Refine Results
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    A Parallel Neural Networks Algorithm for the Clique Partitioning Problem by Harmanani, Haidar M.

    Published 2002
    “…The proposed algorithm has a time complexity of O(1) for a neural network with n vertices and c cliques. …”
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  2. 2

    A FUZZY EVOLUTIONARY ALGORITHM FOR TOPOLOGY DESIGN OF CAMPUS NETWORKS by Youssef, H.

    Published 2020
    “…In this paper, we present a Simulated Evolution algorithm for the design of campus network topology. …”
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  3. 3

    Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm by Youssef, H.

    Published 2020
    “…The problem consists of deciding the number, types, and locations of the network active elements (hubs, switches, and routers), as well as the links and their capacities. …”
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  4. 4

    Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm by Youssef, H.

    Published 2020
    “…The problem consists of deciding the number, types, and locations of the network active elements (hubs, switches, and routers), as well as the links and their capacities. …”
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    article
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    Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network by Mohammad Reza Chalak Qazani (13893261)

    Published 2024
    “…Computational techniques, like the finite element method, are used to analyse behaviours based on varied input parameters. …”
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    Large language models for code completion: A systematic literature review by Rasha Ahmad Husein (19744756)

    Published 2024
    “…Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”
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    Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification by Rajendra Babu Chikkala (22330876)

    Published 2025
    “…In this study, we introduce an innovative method for the multi-classification of breast cancer histopathological images utilizing Bidirectional Recurrent Neural Networks (BRNN). The BRNN structure consists of four unique elements: the backbone branch for transfer learning, the Gated Recurrent Unit (GRU), the residual collaborative branch, and the feature fusion module. …”
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    Nonlinear analysis of shell structures using image processing and machine learning by M.S. Nashed (16392961)

    Published 2023
    “…We show that the results of the trained network agree well with the results of the nonlinear finite element analysis. …”
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    Fuzzy simulated evolution algorithm for topology design of campusnetworks by Youssef, H.

    Published 2000
    “…We present an approach based on the simulated evolution algorithm for the design of campus network topology. …”
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  14. 14

    Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach by Sarif, Bambang

    Published 2006
    “…Multiple-Valued Logic (MVL) has been used in the design of a number of logic systems, including memory, multi-level data communication coding, and a number of special purpose digital processors. …”
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    Optimized FPGA Implementation of PWAM-Based Control of Three—Phase Nine—Level Quasi Impedance Source Inverter by Syed Rahman (569240)

    Published 2019
    “…Since, PWAM control algorithm is more complex than PSCPWM, FPGA based implementation for PWAM control is discussed. …”
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    Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars by Abathar Al-Hamrani (16494884)

    Published 2023
    “…Finally, a design equation that can predict the shear capacity of one-way BFRC-BFRP slabs was proposed based on genetic algorithm. The proposed model showed the best prediction accuracy compared to the available design codes and guidelines with a mean of predicted to experimental shear capacities (V<sub>pred</sub>/V<sub>exp</sub>) ratio of 0.97 and a coefficient of variation of 17.91%.…”
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