Showing 1 - 20 results of 95 for search '(( alignment network algorithm ) OR ((( data code algorithm ) OR ( based evolution algorithms ))))', query time: 0.13s Refine Results
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    Stochastic evolution algorithm for technology mapping by Al-Mulhem, A.S.

    Published 1998
    “…SELF-Map is based on the Stochastic Evolution (SE) algorithm. …”
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    article
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    Accurate multiple network alignment through context-sensitive random walk by Hyundoo Jeong (3840013)

    Published 2015
    “…Until now, a number of network alignment algorithms have been proposed based on different formulations and approaches, many of them focusing on pairwise alignment. …”
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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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    article
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    Fuzzy simulated evolution algorithm for multi-objectiveoptimization of VLSI placement by Sait, Sadiq M.

    Published 1999
    “…A fuzzy simulated evolution algorithm is presented for multi-objective minimization of VLSI cell placement problem. …”
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    article
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    Development of an Optimization Algorithm for Internet Data Traffic by Misbahuddin, Syed

    Published 2020
    “…The algorithm monitors data repetitions in IP datagram and prepares a compression code in response of this repetition. …”
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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
    “…In this paper, we present an approach based on Simulated Evolution algorithm for the design of SEN topology. …”
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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
    “…In this paper, we present an approach based on Simulated Evolution algorithm for the design of SEN topology. …”
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    article
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    A hybridization of evolution strategies with iterated greedy algorithm for no-wait flow shop scheduling problems by Bilal Khurshid (16715865)

    Published 2024
    “…To address the complexity of this NP-hard problem, the HES-IG algorithm combines evolution strategies (ES) and iterated greedy (IG) algorithm, as hybridizing algorithms helps different algorithms mitigate their weaknesses and leverage their respective strengths. …”
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    Practical single node failure recovery using fractional repetition codes in data centers by Itani, May

    Published 2016
    “…FR codes consist of a concatenation of an outer maximum distance separable (MDS) code and an inner fractional repetition code that splits the data into several blocks and stores multiple replicas of each on different nodes in the system. …”
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    Enhanced simulated evolution algorithm for digital circuit design yielding faster execution in a larger solution space by Sait, Sadiq M.

    Published 2004
    “…Evolutionary algorithms have been studied by several researchers for the design of digital circuits. …”
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    article
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    UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data by Behrouz Ahadzadeh (19757022)

    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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    Predicting Android Malware Using Evolution Networks by Chahine, Joy

    Published 2025
    “…This issue requires the development of efficient solutions in order to keep up with the continuous evolution of malware. With this aim, we introduce evolutionary networks, and particularly the Susceptible-Infectious-Susceptible (SIS) model, as a way to address the limitations of previous studies which are typically based on traditional machine learning models. …”
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    masterThesis
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    Differential Evolution and Its Applications in Image Processing Problems: A Comprehensive Review by Chakraborty, Sanjoy

    Published 2022
    “…Differential evolution (DE) is one of the highly acknowledged population-based optimization algorithms due to its simplicity, user-friendliness, resilience, and capacity to solve problems. …”
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