Showing 21 - 40 results of 399 for search '(((( developing based algorithm ) OR ( elements data algorithm ))) OR ( data colony algorithm ))', query time: 0.13s Refine Results
  1. 21

    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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  2. 22

    Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering by Abu Zitar, Raed

    Published 2022
    “…However, the traditional AOA faces some limitations in its search process. Thus, we develop a new variant of the AOA, namely, Augmented AOA (AAOA), integrated with the opposition-based learning (OLB) and Lévy flight (LF) distribution. …”
  3. 23

    AI and IoT-based concrete column base cover localization and degradation detection algorithm using deep learning techniques by Khalid, Naji

    Published 2023
    “…This paper proposes a novel automated algorithm for the health monitoring of concrete column base cover degradation based on IoT and the state-of-the-art deep learning framework, Convolutional Neural Network (CNN). …”
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    article
  4. 24

    Using artificial bee colony to optimize software quality estimation models. (c2015) by Abou Assi, Tatiana Antoine

    Published 2016
    “…We validate our technique on data describing maintainability and reliability of classes in an Object-Oriented system. …”
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    masterThesis
  5. 25

    Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology by Senyuk, Mihail

    Published 2023
    “…In this study, the emergency control algorithms based on ensemble machine learning algorithms (XGBoost and Random Forest) were developed for a low-inertia power system. …”
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    article
  6. 26

    Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms by Arafat Rahman (8065562)

    Published 2021
    “…These results outperform the individual modalities with a significant margin (~5%). We also developed a binary template matching-based algorithm, which gives 93.64% accuracy 6X faster. …”
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    Sample intelligence-based progressive hedging algorithms for the stochastic capacitated reliable facility location problem by Nezir Aydin (8355378)

    Published 2024
    “…We present the effectiveness of the developed integrated approaches, Sampling Based Progressive Hedging Algorithm (SBPHA) and Discarding SBPHA (d-SBPHA), over the pure strategies (i.e. …”
  9. 29

    Real-Time Selective Harmonic Mitigation Technique for Power Converters Based on the Exchange Market Algorithm by Abraham Marquez Alcaide (18582451)

    Published 2020
    “…<p dir="ltr">Hand-in-hand with the smart-grid paradigm development, power converters used in high-power applications are facing important challenges related to efficiency and power quality. …”
  10. 30

    Genetic-Algorithm-Based Neural Network for Fault Detection and Diagnosis: Application to Grid-Connected Photovoltaic Systems by Amal Hichri (21383672)

    Published 2022
    “…This is addressed such that the genetic algorithm (GA) technique is used for selecting the best features and the artificial neural network (ANN) classifier is applied for fault diagnosis. …”
  11. 31

    Detecting sleep outside the clinic using wearable heart rate devices by Ignacio Perez-Pozuelo (14153007)

    Published 2022
    “…We developed and tested a heart rate-based algorithm that captures inter- and intra-individual sleep differences in free-living conditions and does not require human input. …”
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    Real-Time Performance Evaluation of a Genetic Algorithm Based Fuzzy Logic Controller for IPM Motor Drives by Nasir Uddin, M.

    Published 2005
    “…This work presents a novel speed control scheme using a genetic-based fuzzy logic controller (GFLC) for an interior permanent-magnet synchronous motor (IPMSM) drive. …”
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    article
  14. 34

    Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function by Mujahid, S.N.

    Published 2020
    “…In this paper, a fuzzy based process targeting model is developed for a product with multi-characteristic. …”
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    article
  15. 35

    Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function by Duffuaa, S. O.

    Published 2020
    “…In this paper, a fuzzy based process targeting model is developed for a product with multi-characteristic. …”
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    article
  16. 36

    High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm by Badreddine Kanouni (23073244)

    Published 2025
    “…The trigonometric function-based sine cosine algorithm (SCA) may solve such problems, but it traps in local optima, making it inappropriate for larger optimization tasks. …”
  17. 37

    An Artificial Neural Network for Online Tuning of Genetic Algorithm Based PI Controller for Interior Permanent Magnet Synchronous Motor–Drive by Rahman, M. A.

    Published 2006
    “…An artificial neural network (ANN) for online tuning of a genetic algorithm based PI controller for interior permanent magnet synchronous motor (IPMSM) drive is presented in this paper. …”
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    article
  18. 38

    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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