يعرض 81 - 100 نتائج من 157 نتيجة بحث عن '(( elements method algorithm ) OR ((( data code algorithm ) OR ( case machine algorithm ))))', وقت الاستعلام: 0.13s تنقيح النتائج
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    The role of Reinforcement Learning in software testing حسب Amr Abo-eleneen (17032284)

    منشور في 2023
    "…However, for some complex software testing scenarios, neither supervised nor unsupervised machine learning techniques were adequate. As such, researchers applied Reinforcement Learning (RL) techniques in some cases. …"
  4. 84

    Finetuning Analytics Information Systems for a Better Understanding of Users: Evidence of Personification Bias on Multiple Digital Channels حسب Bernard J. Jansen (7434779)

    منشور في 2023
    "…<p dir="ltr">Although the effect of hyperparameters on algorithmic outputs is well known in machine learning, the effects of hyperparameters on information systems that produce user or customer segments are relatively unexplored. …"
  5. 85

    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. 86

    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
  7. 87

    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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    Nonlinear analysis of shell structures using image processing and machine learning حسب M.S. Nashed (16392961)

    منشور في 2023
    "…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …"
  10. 90

    Novel Multi Center and Threshold Ternary Pattern Based Method for Disease Detection Method Using Voice حسب Turker Tuncer (16677966)

    منشور في 2020
    "…The artificial neural network (ANN), support vector machine (SVM) and deep learning models, especially the convolutional neural network (CNN), are the most commonly used machine learning approaches where they proved to be performance in most cases. …"
  11. 91

    CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children حسب Jayakanth Kunhoth (14158908)

    منشور في 2023
    "…The extracted CNN features are then fused in different combinations. Three machine learning algorithms support vector machine (SVM), AdaBoost, and Random forest are employed to assess the performance of the CNN features and fused CNN features. …"
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    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. 94

    Predictive modelling in times of public health emergencies: patients’ non-transport decisions during the COVID-19 pandemic حسب Hassan Farhat (9000509)

    منشور في 2025
    "…</p><h3>Methods</h3><p dir="ltr">Using Python® programming language, this study employed various supervised machine-learning algorithms, including parametric probabilistic models, such as logistic regression, and non-parametric models, including decision trees, random forest (RF), extra trees, AdaBoost, and k-nearest neighbours (KNN), using a dataset of non-transported patients (refused transport and did not receive treatment versus those who refused transport and received treatment) between 2018 and 2022. …"
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    CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children حسب Jayakanth, Kunhoth

    منشور في 2023
    "…The extracted CNN features are then fused in different combinations. Three machine learning algorithms support vector machine (SVM), AdaBoost, and Random forest are employed to assess the performance of the CNN features and fused CNN features. …"
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    article
  17. 97

    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. …"
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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.…"
  19. 99

    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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