يعرض 61 - 80 نتائج من 119 نتيجة بحث عن '(( element method algorithm ) OR ((( data code algorithm ) OR ( meta learning algorithm ))))', وقت الاستعلام: 0.12s تنقيح النتائج
  1. 61

    Machine learning for predicting outcomes of transcatheter aortic valve implantation: A systematic review حسب Ruba Sulaiman (17734065)

    منشور في 2025
    "…Most of the included studies focused on mortality prediction, utilizing datasets of varying sizes and diverse ML algorithms. The most employed ML algorithms were random forest, logistics regression, and gradient boosting. …"
  2. 62

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

    منشور في 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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  3. 63
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    A systematic review of recent advances in the application of machine learning in membrane-based gas separation technologies حسب Farideh Abdollahi (22303153)

    منشور في 2024
    "…The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used to develop the review. …"
  5. 65

    Acoustic Based Localization of Partial Discharge Inside Oil-Filled Transformers حسب Hamidreza Besharatifard (16904823)

    منشور في 2022
    "…<p dir="ltr">This paper addresses the localization of Partial Discharge through a 3D Finite Element Method analysis of acoustic wave propagation inside a 3-phase 35kV transformer with the help of COMSOL Multiphysics software. …"
  6. 66

    Artificial Intelligence in Predicting Cardiac Arrest: Scoping Review حسب Asma Alamgir (18288895)

    منشور في 2021
    "…Most of the studies used data sets with a size of <10,000 samples (32/47, 68%). Machine learning models were the most prominent branch of AI used in the prediction of cardiac arrest in the studies (38/47, 81%), and the most used algorithm was the neural network (23/47, 49%). …"
  7. 67

    Practical Multiple Node Failure Recovery in Distributed Storage Systems حسب Itani, M.

    منشور في 2016
    "…The fractional repetition (FR) code is a class of regenerating codes that consists of a concatenation of an outer maximum distance separable (MDS) code and an inner fractional repetition code that splits the data into several blocks and stores multiple replicas of each on different nodes in the system. …"
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    conferenceObject
  8. 68

    Design Optimization of Inductive Power Transfer Systems Considering Bifurcation and Equivalent AC Resistance for Spiral Coils حسب Alireza Namadmalan (16864236)

    منشور في 2020
    "…Equivalent AC resistance of spiral coils is modeled based on eddy currents simulations using Finite Element Method (FEM) and Maxwell simulator. Based on the FEM simulations, a new approximation method using separation of variables is proposed as a function of spiral coil's main parameters. …"
  9. 69

    A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method حسب Shahid Rahman (16904613)

    منشور في 2022
    "…Every communication body wants to secure their data while communicating over the Internet. The internet has various benefits but the main demerit is the privacy and security and the transmission of data over insecure network or channel may happen. …"
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    A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks حسب Sakib Mahmud (15302404)

    منشور في 2025
    "…We identify promising directions: hybrid model-free and model-based DRL, offline-to-online learning, transfer and meta-learning for rapid adaptation, integration with federated learning and blockchain for privacy and trust, and progress in interpretability, uncertainty quantification, and formal safety guarantees. …"
  12. 72

    Enhanced Deep Belief Network Based on Ensemble Learning and Tree-Structured of Parzen Estimators: An Optimal Photovoltaic Power Forecasting Method حسب Mohamed Massaoudi (16888710)

    منشور في 2021
    "…The proposed forecasting tool incorporates a base model and meta-model layers. The first-layer base learner combines extreme learning machines, extremely randomized trees, k-nearest neighbor, and mondrian forest models. …"
  13. 73

    Correlation Clustering with Overlaps حسب Fakhereldine, Amin

    منشور في 2020
    "…In other words, data elements (or vertices) will be allowed to be members in more than one cluster instead of limiting them to only one single cluster, as in classical clustering methods. …"
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    masterThesis
  14. 74
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    Integrated whole transcriptome and small RNA analysis revealed multiple regulatory networks in colorectal cancer حسب Hibah Shaath (5599658)

    منشور في 2021
    "…Additionally, potential interaction between differentially expressed lncRNAs such as H19, SNHG5, and GATA2-AS1 with multiple miRNAs has been revealed. Taken together, our data provides thorough analysis of dysregulated protein-coding and non-coding RNAs in CRC highlighting numerous associations and regulatory networks thus providing better understanding of CRC.…"
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    Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification حسب Rajendra Babu Chikkala (22330876)

    منشور في 2025
    "…<p dir="ltr">In recent years, deep learning methods have dramatically improved medical image analysis, though earlier models faced difficulties in capturing intricate spatial and contextual details. …"
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    Artificial intelligence-based methods for fusion of electronic health records and imaging data حسب Farida Mohsen (16994682)

    منشور في 2022
    "…In our analysis, a typical workflow was observed: feeding raw data, fusing different data modalities by applying conventional machine learning (ML) or deep learning (DL) algorithms, and finally, evaluating the multimodal fusion through clinical outcome predictions. …"
  20. 80

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

    منشور في 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.…"