يعرض 121 - 140 نتائج من 157 نتيجة بحث عن '(( algorithm fc function ) OR ((( algorithm model function ) OR ( algorithm models function ))))', وقت الاستعلام: 0.12s تنقيح النتائج
  1. 121

    Vibration suppression in a cantilever beam using a string-type vibration absorber حسب Issa, Jimmy S.

    منشور في 2017
    "…In the first, the spring stiffness, the position of the second attachment point of the string and a preliminary damping constant are calculated using a genetic algorithm approach where the objective function is the maximum displacement on the beam. …"
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    conferenceObject
  2. 122

    Diagnostic structure of visual robotic inundated systems with fuzzy clustering membership correlation حسب Hariprasath Manoharan (14157966)

    منشور في 2023
    "…Additionally, a clustering algorithm with a fuzzy membership function is implemented, allowing the robots to advance in accordance with predefined clusters and arrive at their starting place within a predetermined amount of time. …"
  3. 123
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    Defense against adversarial attacks: robust and efficient compressed optimized neural networks حسب Insaf Kraidia (19198012)

    منشور في 2024
    "…<p dir="ltr">In the ongoing battle against adversarial attacks, adopting a suitable strategy to enhance model efficiency, bolster resistance to adversarial threats, and ensure practical deployment is crucial. …"
  5. 125

    Reinforcement Learning-Based School Energy Management System حسب Yassine Chemingui (18891757)

    منشور في 2020
    "…In recent years, the Deep Reinforcement Learning algorithm, applying neural networks for function approximation, shows promising results in handling such complex problems. …"
  6. 126

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

    منشور في 2024
    "…Furthermore, the confusion matrix validates the random forest classification model's accuracy. At the same time, the mean square error value serves as the loss function for the ANN model (i.e., the loss function values were 2.84 × 10<sup>−7</sup> and 6.40 × 10<sup>−7</sup>, respectively, for X1 and X2 loading conditions at 45° angle). …"
  7. 127

    Regression testing web services-based applications حسب Tarhini, Abbas

    منشور في 2006
    "…Such applications are usually modified to fix errors or to enhance their functionality. After modifications, regression testing is essential to ensure that modifications do not lead to adverse effects. …"
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    conferenceObject
  8. 128

    Detecting latent classes in tourism data through response-based unit segmentation (REBUS) in Pls-Sem حسب Assaker, Guy

    منشور في 2016
    "…This research note describes Response-Based Unit Segmentation (REBUS), a “latent class detection” technique used in partial least squares–structural equation modeling (PLS-SEM) to examine data heterogeneity. The research note is presented in two parts: Part A presents an overview of REBUS, including its development, algorithm, and its primary functions. …"
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    article
  9. 129

    A lightweight adaptive compression scheme for energy-efficient mobile-to-mobile file sharing applications حسب Sharafeddine, Sanaa

    منشور في 2011
    "…Moreover, we derive an empirical energy model that analytically quantifies the energy consumed during data transmission as a function of the signal strength level and during data compression as a function of the data size. …"
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    article
  10. 130

    A Hybrid Transfer Learning Approach to Teeth Diagnosis Using Orthopantomogram Radiographs حسب Alabd-Aljabar, Ahmed

    منشور في 2024
    "…To showcase the performance of such algorithms, we propose two approaches for the task of teeth diagnosis utilizing Orthopantomograms (panoramic radiographs): 1) a direct classification approach; and 2) a hybrid approach that combines a deep learning model with a traditional classifier. …"
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    article
  11. 131

    Recursive Parameter Identification Of A Class Of Nonlinear Systems From Noisy Measurements حسب Emara-Shabaik, Husam

    منشور في 2020
    "…The convergence analysis of the proposed recursive identification algorithm utilizes stochastic Lyapunov functions. Sufficient conditions for the almost sure convergence of the estimated parameters to the true ones are obtained.…"
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    article
  12. 132
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  14. 134

    LNCRI: Long Non-Coding RNA Identifier in Multiple Species حسب Saleh Musleh (15279190)

    منشور في 2021
    "…We applied the SHAP algorithm to demonstrate the importance of most dominating features that were leveraged in the model. …"
  15. 135

    A novel network-based SIS framework for improved GA performance حسب Tohme, Rawane

    منشور في 2025
    "…To address these challenges, this work introduces SIS-NGA which integrates the Susceptible-Infected-Susceptible (SIS) epidemic model and Genetic Algorithms within a scale-free network topology, to guide the search for optimal solutions. …"
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    masterThesis
  16. 136

    Integration of nonparametric fuzzy classification with an evolutionary-developmental framework to perform music sentiment-based analysis and composition حسب Abboud, Ralph

    منشور في 2019
    "…Unlike existing solutions, MUSEC is: (i) a hybrid crossover between supervised learning (SL, to learn sentiments from music) and evolutionary computation (for music composition, MC), where SL serves at the fitness function of MC to compose music that expresses target sentiments, (ii) extensible in the panel of emotions it can convey, producing pieces that reflect a target crisp sentiment (e.g., love) or a collection of fuzzy sentiments (e.g., 65% happy, 20% sad, and 15% angry), compared with crisp-only or two-dimensional (valence/arousal) sentiment models used in existing solutions, (iii) adopts the evolutionary-developmental model, using an extensive set of specially designed music-theoretic mutation operators (trille, staccato, repeat, compress, etc.), stochastically orchestrated to add atomic (individual chord-level) and thematic (chord pattern-level) variability to the composed polyphonic pieces, compared with traditional evolutionary solutions producing monophonic and non-thematic music. …"
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    article
  17. 137

    Fleet sizing of trucks for an inter-facility material handling system using closed queueing networks حسب Mohamed Amjath (17542512)

    منشور في 2022
    "…This study proposes an analytical method based on sequential quadratic programming (SQP) methodology coupled with a mean value analysis (MVA) algorithm to solve this NP-Hard problem. Furthermore, a discrete event simulation (DES) model is developed to validate the optimisation of non-dominant solutions. …"
  18. 138

    An Introduction to the Special Issue “Protein Glycation in Food, Nutrition, Health and Disease” حسب Naila Rabbani (291722)

    منشور في 2022
    "…The keynote speaker was Lasker Laureate Professor Kazutoshi Mori, speaking on the unfolded protein response, and there were sessions on: glycation in obesity, diabetes, and diabetic complications; glycation in food; glycation through the life course—from maternal bonding to aging; glycation in plants—physiology, function, and food security; glycation in the COVID-19 response; glycation analytics and chemistry; glycation in kidney disease, cancer, and mental health; glycation-related imaging, diagnostic algorithms, and therapeutics; and methods and models in glycation research. …"
  19. 139

    Autism Detection of MRI Brain Images Using Hybrid Deep CNN With DM-Resnet Classifier حسب JAIN, SWETA

    منشور في 2023
    "…The hyper parameters are optimized with DM optimization algorithm which improves the accuracy of classifier. …"
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  20. 140

    Determining the Factors Affecting the Boiling Heat Transfer Coefficient of Sintered Coated Porous Surfaces حسب Uzair Sajjad (19646296)

    منشور في 2021
    "…In this regard, two Bayesian optimization algorithms including Gaussian process regression (GPR) and gradient boosting regression trees (GBRT) are used for tuning the hyper-parameters (number of input and dense nodes, number of dense layers, activation function, batch size, Adam decay, and learning rate) of the deep neural network. …"