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Showing 101 - 120 results of 820 for search '(((( data finding algorithm ) OR ( models using algorithm ))) OR ( element based algorithm ))', query time: 0.13s Refine Results
  1. 101

    Sentiment Analysis of the Emirati Dialect text using Ensemble Stacking Deep Learning Models by AL SHAMSI, ARWA AHMED

    Published 2023
    “…For the basic machine learning algorithms, LR, NB, SVM, RF, DT, MLP, AdaBoost, GBoost, and an ensemble model of machine learning classifiers were used. …”
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  2. 102

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

    Published 2016
    “…We compare our models to others constructed using other well established techniques such as C4.5, Genetic Algorithms, Simulated Annealing, Tabu Search, multi-layer perceptron with back-propagation, multi-layer perceptron hybridized with ABC and the majority classifier. …”
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    masterThesis
  3. 103
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  5. 105

    Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

    Published 2023
    “…Therefore, in this study, we conduct a performance evaluation and comparison for various DL algorithms (LSTM, GRU, LSTM-ATT, CNN-BLSTM, CNN-LSTM and LSTM-TCN) on different datasets of Arabic cyberbullying to obtain more precise and dependable findings. …”
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  6. 106

    Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

    Published 2023
    “…Therefore, in this study, we conduct a performance evaluation and comparison for various DL algorithms (LSTM, GRU, LSTM-ATT, CNN-BLSTM, CNN-LSTM and LSTM-TCN) on different datasets of Arabic cyberbullying to obtain more precise and dependable findings. …”
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  7. 107

    Portfolio Selection Problem Using CVaR Risk Measures Equipped with DEA, PSO, and ICA Algorithms by Abdelouahed Hamdi (14158899)

    Published 2022
    “…Therefore, in this study we examined this market based on the price index of the automotive group, then optimized a portfolio of automotive companies using two methods. In the first method, the CVaR measurement was modeled by means of DEA, then Particle Swarm Optimization (PSO) and the Imperial Competitive Algorithm (ICA) were used to solve the proposed model. …”
  8. 108

    Classifying Maqams of Qur'anic Recitations Using Deep Learning by Shahriar, Sakib

    Published 2021
    “…Technological advancement can be utilized for automatic classification of these melodies which can then be used by students for self-learning. Using state-of-the-art deep learning algorithms, this research focuses on the classification of the eight popular maqamat (plural of maqam). …”
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    article
  9. 109

    YOLO-DefXpert: An Advanced Defect Detection on PCB Surfaces Using Improved YOLOv11 Algorithm by Prabu Selvam (22330264)

    Published 2025
    “…This study introduces an improved PCB defect detection model, YOLO-DefXpert, using the YOLOv11 algorithm to address the low accuracy and efficiency challenges in detecting tiny-sized defects on PCBs. …”
  10. 110
  11. 111

    Minimizing using BBO and DFO methods by El Zeghondy, Jean

    Published 2022
    “…The goal of this thesis is to develop two MATLAB codes for the numerical algorithm of [1]. To solve nonlinear differential equations we use Runge-Kutta method of fourth order, and for the minimization part, we use two different methods, namely Nelder-Mead and Model Based Descent methods. …”
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    masterThesis
  12. 112
  13. 113

    A Novel Genetic Algorithm Optimized Adversarial Attack in Federated Learning for Android-Based Mobile Systems by Faria Nawshin (21841598)

    Published 2025
    “…<p dir="ltr">Federated Learning (FL) is gaining traction in Android-based consumer electronics, enabling collaborative model training across decentralized devices while preserving data privacy. …”
  14. 114

    Modelling Exchange Rates during Currency Crisis using Neural Networks by Nasr, G. E.

    Published 2006
    “…This paper presents an artificial neural network (ANN) approach to the forecasting of exchange rate movements during periods of currency crises characterized by excessive volatility. The models are built using the feedforward ANN structure trained by the backpropagation algorithm. …”
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    conferenceObject
  15. 115

    Internal Model Control Structure Using Adaptive Inverse Control Strategy by Shafiq, M.Riyaz

    Published 2003
    “…In this paper, we propose a new adaptive IMC scheme based on adaptive finite impulse response filters, which can be designed for both minimum and non-minimum phase systems in the same fashion. The internal model of the plant is estimated by recursive least square algorithm and the inverse of the system by least mean square. …”
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    article
  16. 116

    Arabic Text Classification Using Modified Artificial Bee Colony Algorithm for Sentiment Analysis: The Case of Jordanian Dialect by Habeeb, Abdallah

    Published 2022
    “…The second phase, modified the Artificial Bee Colony (ABC) Algorithm, with Upper Confidence Bound (UCB) Algorithm, to promote the exploitation ability for the minimum dimension, to get the minimum number of the optimal feature, then using forward feature selection strategy by four classifiers of machine learning algorithms: (K-Nearest Neighbors (KNN), Support vector machines (SVM), Naïve-Bayes (NB), and Polynomial Neural Networks (PNN). …”
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  17. 117

    Stochastic Programming for Hub Energy Management Considering Uncertainty Using Two-Point Estimate Method and Optimization Algorithm by Ali S. Alghamdi (17541711)

    Published 2023
    “…In this study, the uncertainty of solar and wind energy sources is modeled using Hang’s two-point estimating method (TPEM). …”
  18. 118

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

    Published 2022
    “…Deep learning is the most promising algorithm compared to another Machine Learning (ML) algorithm. …”
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  19. 119

    A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti (21593819)

    Published 2025
    “…Three different publicly available datasets have been used based on the age group to create the best predicting model for each case. …”
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