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Showing 141 - 160 results of 196 for search '(( element method algorithm ) OR ((( data encoding algorithm ) OR ( based training algorithms ))))', query time: 0.10s Refine Results
  1. 141

    Online dynamic ensemble deep random vector functional link neural network for forecasting by Ruobin Gao (16003195)

    Published 2023
    “…<p>This paper proposes a three-stage online deep learning model for time series based on the ensemble deep random vector functional link (edRVFL). …”
  2. 142

    Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network by Monzure-Khoda Kazi (17191207)

    Published 2024
    “…The results demonstrate that the suggested RF-ANN-based technique can predict the optimal composite design with high accuracy (precision, recall, and f1-score for test and train dataset were 1). …”
  3. 143

    A New Approach for Recognizing Saudi Arabian License Plates using Neural Networks by Deriche, Mohamed

    Published 2020
    “…Finally, a Multilayer Feedforward Neural Network (MFNN) with a backpropagation (BP) algorithm is used for character recognition. We discuss new features from the characters for training the NN. …”
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  4. 144

    A Novel Deep Learning Technique for Detecting Emotional Impact in Online Education by Abu Zitar, Raed

    Published 2022
    “…For validation of the proposed system, an online course with students is used; the findings suggest that this technique operates well. Based on emotional analysis, several deep learning techniques are applied to train and test the emotion classification process. …”
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  5. 145

    Query acceleration in distributed database systems by Haraty, Ramzi A.

    Published 2001
    “…Query optimization strategies aim to minimize the cost of transferring data across networks. Many techniques and algorithms have been proposed to optimize queries. …”
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  6. 146
  7. 147

    Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images by Rehan Raza (17019105)

    Published 2023
    “…Moreover, it is faster and requires fewer parameters to train than other CNN based models, making it a good choice for large-scale deployment in clinical settings and a promising tool for automated lung cancer diagnosis from CT scan images.…”
  8. 148

    Supervised term-category feature weighting for improved text classification by Attieh, Joseph

    Published 2022
    “…GradientDescentANN replaces the iterative additive process mentioned previously by computing the term-category matrix using a gradient descent ANN model. Training the ANN using the gradient descent algorithm allows updating the term-category matrix until reaching convergence. …”
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  9. 149

    An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study by Ayman Hassan (14426412)

    Published 2024
    “…We aimed to develop an app using a comprehensive geomapping navigation and estimation system based on machine learning algorithms. This app uses key stroke-related timelines including the last time the patient was known to be well, patient location, treatment options, and imaging availability at different health care facilities.…”
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  12. 152

    Artificial Intelligence for Skin Cancer Detection: Scoping Review by Abdulrahman Takiddin (14153181)

    Published 2021
    “…Hence, to aid in diagnosing skin cancer, artificial intelligence (AI) tools are being used, including shallow and deep machine learning–based methodologies that are trained to detect and classify skin cancer using computer algorithms and deep neural networks.…”
  13. 153

    Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort by Sergio Márquez-Sánchez (19437985)

    Published 2023
    “…Moreover, the prevalent cloud-based nature of these systems introduces elevated cybersecurity risks and substantial data transmission overheads. …”
  14. 154

    Random vector functional link network: Recent developments, applications, and future directions by A.K. Malik (16003193)

    Published 2023
    “…Generally, the back propagation (BP) based iterative approaches are used to train the neural networks, however, it results in the issues of local minima, sensitivity to learning rate and slow convergence. …”
  15. 155

    Gene-specific machine learning model to predict the pathogenicity of BRCA2 variants by Mohannad N. Khandakji (13885434)

    Published 2022
    “…The model utilizes general variant information such as position, frequency, and consequence for the canonical BRCA2 transcript, as well as deleteriousness prediction scores from several tools. We trained the model on 80% of the expert reviewed variants by the Evidence-Based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) consortium and tested its performance on the remaining 20%, as well as on an independent set of variants of uncertain significance with experimentally determined functional scores.…”
  16. 156
  17. 157

    Development of Machine Learning Models for Studying the Premixed Turbulent Combustion of Gas-To-Liquids (GTL) Fuel Blends by Abdellatif M. Sadeq (16931841)

    Published 2024
    “…The k-fold cross-validation technique is used for model training, and the developed neural network-based model is used to investigate the effects of operating parameters on the premixed turbulent flames. …”
  18. 158

    CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children by Jayakanth, Kunhoth

    Published 2023
    “…Transfer learning is applied using a pre-trained DenseNet201 network to develop four distinct CNN models separately trained on word, pseudoword, difficult word, and sentence images. …”
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  19. 159

    Diabetic Sensorimotor Polyneuropathy Severity Classification Using Adaptive Neuro Fuzzy Inference System by Fahmida Haque (16896489)

    Published 2021
    “…This study also investigates the changes in muscle activity during gait from three different lower limb muscles (vastus lateralis (VL), tibialis anterior (TA), and gastrocnemius medialis (GM)) electromyography (EMG) of DSPN patients with different severity levels classified by the proposed classifier and observed that VL and GM muscles show an increase in delay for activation peak and decrease in peak magnitude during gait with the progression of DSPN severity. Based on this observation, the ANFIS model was trained using the extracted EMG features for DSPN severity stratification and showed promising results. …”
  20. 160