Showing 1 - 20 results of 27 for search '(((( implementing colony algorithm ) OR ( element aya algorithm ))) OR ( level coding algorithm ))', query time: 0.13s Refine Results
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    Using artificial bee colony to optimize software quality estimation models. (c2015) by Abou Assi, Tatiana Antoine

    Published 2016
    “…In order to measure such software quality characteristics, we must wait until the software is implemented, tested and put to use for a certain amount of time. …”
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    masterThesis
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    ANT-colony optimization-direct torque control for a doubly fed induction motor : An experimental validation by Said Mahfoud (17150968)

    Published 2022
    “…For that reason, this work is focused on the theoretical studies and experimental validation on dSPACE Board DS1104 of the new proposed approach based on PID speed regulation, optimized by the Ant Colony Optimization algorithm (ACO) for DTC, applied to both sides of the Doubly Fed Induction Motor (DFIM), to overcome the previous drawbacks cited at the beginning. …”
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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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    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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    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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    Recent advances on artificial intelligence and learning techniques in cognitive radio networks by Abbas, Nadine

    Published 2015
    “…The literature survey is organized based on different artificial intelligence techniques such as fuzzy logic, genetic algorithms, neural networks, game theory, reinforcement learning, support vector machine, case-based reasoning, entropy, Bayesian, Markov model, multi-agent systems, and artificial bee colony algorithm. …”
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    article
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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. …”