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Showing 1 - 20 results of 179 for search '(( element network algorithm ) OR ((( data rd algorithm ) OR ( based making algorithm ))))', query time: 0.17s Refine Results
  1. 1

    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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    article
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    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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    article
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    A matrix-based damage assessment and recovery algorithm by Haraty, Ramzi A.

    Published 2014
    “…In this work we present efficient damage assessment and recovery algorithms to recover from malicious transactions in a database based on the concept of the matrix. …”
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    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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    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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    An image processing and genetic algorithm-based approach for the detection of melanoma in patients by Tokajian, Sima

    Published 2018
    “…The second phase classifies lesions using a Genetic Algorithm. Our technique shows a significant improvement over other well-known algorithms and proves to be more stable on both training and testing data.…”
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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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    Enhancing fairness and scalability in IOTA tangle networks: a POMDP-based tip selection algorithm for decentralized systems by Mays Alshaikhli (22564811)

    Published 2025
    “…This algorithm offers significant scalability, fairness, and adaptability, making it a robust solution for IoT-based decentralized applications. …”
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    Real-Time Performance Evaluation of a Genetic Algorithm Based Fuzzy Logic Controller for IPM Motor Drives by Nasir Uddin, M.

    Published 2005
    “…The proposed GFLC is developed to have less computational burden, which makes it suitable for real-time implementation. The parameters for the GFLC are tuned by genetic algorithm (GA). …”
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    High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm by Badreddine Kanouni (23073244)

    Published 2025
    “…The trigonometric function-based sine cosine algorithm (SCA) may solve such problems, but it traps in local optima, making it inappropriate for larger optimization tasks. …”
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    TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection by Zina Chkirbene (16869987)

    Published 2020
    “…TIDCS reduces the number of features in the input data based on a new algorithm for feature selection. Initially, the features are grouped randomly to increase the probability of making them participating in the generation of different groups, and sorted based on their accuracy scores. …”
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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. …”