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Showing 101 - 120 results of 573 for search '(( element data algorithm ) OR ((( data processing algorithm ) OR ( based learning algorithm ))))', query time: 0.14s Refine Results
  1. 101

    Multiclass feature selection with metaheuristic optimization algorithms: a review by Abu Zitar, Raed

    Published 2022
    “…Metaheuristic algorithms have also been presented in four primary behavior-based categories, i.e., evolutionary-based, swarm-intelligence-based, physics-based, and human-based, even though some literature works presented more categorization. …”
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  2. 102

    Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing by Jincheng Zhou (1887307)

    Published 2023
    “…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …”
  3. 103

    Wind, Solar, and Photovoltaic Renewable Energy Systems with and without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques by Abu Zitar, Raed

    Published 2022
    “…This paper covered the most resent and important researchers in the domain of renewable problems using the learning-based methods. Various types of Deep Learning (DL) and Machine Learning (ML) algorithms employed in Solar and Wind energy supplies are given. …”
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  4. 104

    NOVEL STACKING CLASSIFICATION AND PREDICTION ALGORITHM BASED AMBIENT ASSISTED LIVING FOR ELDERLY by JINESH, PADIKKAPPARAMBIL

    Published 2022
    “…Therefore, this thesis proposed a Novel Stacking Classification and Prediction (NSCP) algorithm based on AAL for the older people with Multi-strategy Combination based Feature Selection (MCFS) and Novel Clustering Aggregation (NCA) algorithms. …”
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    A fast exact sequential algorithm for the partial digest problem by Mostafa M. Abbas (17058093)

    Published 2016
    “…Two types of simulated data, random and Zhang, are used to measure the efficiency of the algorithm. …”
  8. 108

    Salak Image Classification Method Based Deep Learning Technique Using Two Transfer Learning Models by Theng, Lau Wei

    Published 2022
    “…There are many techniques that can be used for fruit classification using computer vision technology. Deep learning is the most promising algorithm compared to another Machine Learning (ML) algorithm. …”
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  9. 109

    Efficient multi-objective neural architecture search framework via policy gradient algorithm by Bo Lyu (16522643)

    Published 2024
    “…<p>Differentiable architecture search plays a prominent role in Neural Architecture Search (NAS) and exhibits preferable efficiency than traditional heuristic NAS methods, including those based on evolutionary algorithms (EA) and reinforcement learning (RL). …”
  10. 110

    Use of Data Mining Techniques to Detect Fraud in Procurement Sector by AL HAMMADI, SUMAYYA ABDULLA

    Published 2022
    “…The method used in this research is a classification of models and algorithms used in data mining. All techniques also will be studied; they include clustering, tracking patterns, classifications and outlier detection. …”
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  11. 111
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    Effective uncertain fault diagnosis technique for wind conversion systems using improved ensemble learning algorithm by Khadija Attouri (18024307)

    Published 2023
    “…<p>This paper introduces a pioneering fault diagnosis technique termed Interval Ensemble Learning based on Sine Cosine Optimization Algorithm (IEL- SCOA), tailored to tackle uncertainties prevalent in wind energy conversion (WEC) systems. …”
  13. 113

    FPGA-Based Network Traffic Classification Using Machine Learning by Elnawawy, Mohammed

    Published 2020
    “…Classification approaches based on machine learning techniques have shown promising results with high levels of accuracy. …”
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    Hybrid Deep Learning-based Models for Crop Yield Prediction by Alexandros Oikonomidis (12050497)

    Published 2022
    “…In this study, we developed deep learning-based models to evaluate how the underlying algorithms perform with respect to different performance criteria. …”
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