Showing 1 - 20 results of 27 for search '(((( select density algorithm ) OR ( elementi per algorithm ))) OR ( level coding algorithm ))', query time: 0.12s Refine Results
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    Combinatorial method for bandwidth selection in wind speed kernel density estimation by El Dakkak, Omar

    Published 2019
    “…In this study, a non-parametric combinatorial method is implemented for obtaining an accurate non-parametric kernel density estimation (KDE)-based statistical model of wind speed, in which the selection of the bandwidth parameter is optimised concerning mean integrated absolute error (L 1 error ) between the true and hypothesised densities. …”
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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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    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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    article
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    Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm by Nasser, Youssef

    Published 2024
    “…This work aims to enhance the performance of the K-means algorithm by introducing a novel method for selecting the initial centroids, thereby minimizing randomness and reducing the number of iterations needed to reach optimal results. …”
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    masterThesis
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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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    Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms by Md Ferdous Wahid (13485799)

    Published 2022
    “…Seven important predictor variables are identified using a supervised feature selection approach: oil and water velocities, FP, input diameter, oil and water density, and oil viscosity. …”
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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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    Evacuation of a highly congested urban city by El Khoury, John

    Published 2017
    “…The algorithm uses Dijkstras algorithm to find the shortest path(s) and a modified greedy algorithm to assign maximum flows to selected paths given a specific schedule per time interval. …”
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    conferenceObject
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    Efficient Seismic Volume Compression using the Lifting Scheme by Khene, M. F.

    Published 2000
    “…Finally a runlength plus a Huffman encoding are applied for binary coding of the quantized coefficients.…”
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    article
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    Downlink channel estimation for IMT-DS by Faisal, S.

    Published 2001
    “…To obtain channel estimates during pilot symbols, we propose a chip level adaptive channel estimation which performs better than the conventional method. …”
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    article
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    Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model by Ramesh Sundar (19326046)

    Published 2024
    “…The performance level improvements are practically summarized in both the transmission and reception entities with the help of the proposed hybrid network architecture and the associated Dual Deep Network algorithm. …”
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    Oversampling techniques for imbalanced data in regression by Samir Brahim Belhaouari (9427347)

    Published 2024
    “…For image datasets, we employ Multi-Level Autoencoders, consisting of Convolutional and Fully Connected Autoencoders. …”