Showing 21 - 40 results of 195 for search '(((( pre processing algorithm ) OR ( element data algorithm ))) OR ( level modeling algorithm ))', query time: 0.14s Refine Results
  1. 21

    A kernelization algorithm for d-Hitting Set by Abu-Khzam, Faisal N.

    Published 2010
    “…For a given parameterized problem, π, a kernelization algorithm is a polynomial-time pre-processing procedure that transforms an arbitrary instance of π into an equivalent one whose size depends only on the input parameter(s). …”
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    Formal synthesis of VLSI layouts from algorithmic specifications by Sait, Sadiq M.

    Published 2020
    “…In this paper we present a formal approach for high level synthesis. This formal high level syntesis system uses recursive algorithms to model the behaviour to be synthesized. …”
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    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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    Impact of Charging Electric Vehicles under Different State of Charge Levels and Extreme Conditions by Claude Ziad El-Bayeh (17542284)

    Published 2021
    “…This paper defines extreme conditions as the state of a load or network that breaks the limits of the constraints in an optimization model. Once these constraints are violated, the optimization algorithm might not work correctly and might not converge to a feasible solution, especially when the complexity of the system increases and includes nonlinearities. …”
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    Defense against adversarial attacks: robust and efficient compressed optimized neural networks by Insaf Kraidia (19198012)

    Published 2024
    “…This study compresses the generative pre-trained transformer (GPT) by 65%, saving time and memory without causing performance loss. …”
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    Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain by Al Sadawi, Alia

    Published 2021
    “…The objective is to minimize different cost types while satisfying constraints such as resources availability, customer service level, and tasks dependency relation. The algorithm proved its effectiveness by allocating tasks with higher priority and weight while taking into consideration customers’ Service Level Agreement, time, and different types of costs, which led to a lower total cost of the batching process. …”
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    Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction by Syed Mohammad (21075689)

    Published 2025
    “…This adjustment highlights the importance of concentration levels in reflecting the variability specific to individual interaction sites. …”
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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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  17. 37

    Genetic Algorithm for Solving Site Layout Problem with Unequal-Size and Constrained Facilities by Zouein, P. P.

    Published 2002
    “…The paper concludes with examples illustrating the strength and limitations of the proposed algorithm in the cases of ~1! loosely versus tightly constrained layouts with equal levels of interaction between facilities; ~2! …”
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    Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition by Dabeeruddin Syed (16864260)

    Published 2021
    “…<p>Different aggregation levels of the electric grid's big data can be helpful to develop highly accurate deep learning models for Short-term Load Forecasting (STLF) in electrical networks. …”
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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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