Showing 1 - 20 results of 25 for search '(((( element consistent algorithm ) OR ( element rf algorithm ))) OR ( neural coding algorithm ))', query time: 0.11s Refine Results
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    On the Optimization of Band Gaps in Periodic Waveguides by Jamil Renno (14070771)

    Published 2025
    “…<h3 dir="ltr">Purpose</h3><p dir="ltr">This work applies a computational framework for vibration attenuation in periodic structures by combining the established wave and finite element (WFE) method with nature-inspired optimization algorithms. …”
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    Fuzzy simulated evolution algorithm for topology design of campusnetworks by Youssef, H.

    Published 2000
    “…The topology design of campus networks is a hard constrained combinatorial optimization problem. It consists of deciding the number, type, and location of the active network elements (nodes) and links. …”
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    A FUZZY EVOLUTIONARY ALGORITHM FOR TOPOLOGY DESIGN OF CAMPUS NETWORKS by Youssef, H.

    Published 2020
    “…ABSTRACT The topology design of campus networks is a hard constrained combinatorial optimization problem. It consists of deciding the number, type, and location of the active network elements (nodes), and the links. …”
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    Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm by Youssef, H.

    Published 2020
    “…Abstract The topology design of switched enterprise networks (SENs) is a hard constrained combinatorial optimization problem. 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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    Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm by Youssef, H.

    Published 2020
    “…Abstract The topology design of switched enterprise networks (SENs) is a hard constrained combinatorial optimization problem. 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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    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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