يعرض 161 - 180 نتائج من 334 نتيجة بحث عن '(((( algorithm i function ) OR ( algorithm using function ))) OR ( algorithms within function ))', وقت الاستعلام: 0.16s تنقيح النتائج
  1. 161

    A combined resource allocation framework for PEVs charging stations, renewable energy resources and distributed energy storage systems حسب Kandil, Sarah M.

    منشور في 2017
    "…The formulation employs a general objective function that optimizes the total Annual Cost of Energy (ACOE). …"
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    article
  2. 162

    The Use of Enumerative Techniques in Topological Optimization of Computer Networks Subject to Fault Tolerance and Reliability حسب Abd-El-barr, Mostafa

    منشور في 2003
    "…Experimental results obtained from a set of randomly generated networks using the proposed algorithms are presented and compared to those obtained using the existing techniques [1], [2]. …"
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    article
  3. 163

    Joint distributed synchronization and positioning in UWB ad hoc networks using TOA حسب Denis, B.

    منشور في 2006
    "…Finally, the proposed distributed maximum log-likelihood algorithm proves to preserve a reasonable level of complexity in each node by approximating asynchronously the positive gradient direction of the log-likelihood function. …"
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    article
  4. 164
  5. 165

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

    منشور في 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
  6. 166
  7. 167

    Intelligent Bilateral Client Selection in Federated Learning Using Game Theory حسب Wehbi, Osama

    منشور في 2022
    "…To overcome this problem, we present in this paper FedMint, an intelligent client selection approach for federated learning on IoT devices using game theory and bootstrapping mechanism. Our solution involves designing (1) preference functions for the client IoT devices and federated servers to allow them to rank each other according to several factors such as accuracy and price, (2) intelligent matching algorithms that take into account the preferences of both parties in their design, and (3) bootstrapping technique that capitalizes on the collaboration of multiple federated servers in order to assign initial accuracy value for the new connected IoT devices. …"
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    masterThesis
  8. 168
  9. 169

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

    منشور في 2024
    "…Fortunately, the availability of modern computing devices has made the automated diagnosis of teeth readily possible using deep learning. Despite this, concerns about the accuracy and function of automated diagnosis remain among patients. …"
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    article
  10. 170

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

    منشور في 2024
    "…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). …"
  11. 171

    A Quasi-Oppositional Method for Output Tracking Control by Swarm-Based MPID Controller on AC/HVDC Interconnected Systems With Virtual Inertia Emulation حسب Iman M. Hosseini Naveh (16891482)

    منشور في 2021
    "…The role of the proposed quasi oppositional based SMPID controller is to modify the tracking strategy on AC/HVDC interconnected systems while reducing the related cost function. The proposed analysis is established considering the most highly cited, well-known tested and newly expanded swarm-based optimization algorithms (SBOAs), such as Grasshopper Optimization Algorithm (GOA), Grey Wolf Optimization (GWO), Artificial Fish Swarm Algorithm (AFSA), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO). …"
  12. 172
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  14. 174

    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
  15. 175
  16. 176

    StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features حسب Muhammad Arif (769250)

    منشور في 2024
    "…Additionally, we applied the local interpretable model-agnostic explanations (LIME) algorithm to understand the contribution of selected features to the overall prediction. …"
  17. 177

    Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network حسب Fares Almomani (12585685)

    منشور في 2020
    "…An ANN model consists of three layers, 15 neutrons and 260 <i>epochs</i> accurately predict the CMP with 99.1% of data within ±10% deviation of the mean experimental value. …"
  18. 178

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

    منشور في 2022
    "…Analytical model results are validated using the simulation results, which are proved to be very accurate, with deviations ranges within ±7%.…"
  19. 179

    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. 180

    Energy utilization assessment of a semi-closed greenhouse using data-driven model predictive control حسب Farhat Mahmood (15468854)

    منشور في 2021
    "…The proposed method consists of a multilayer perceptron model representing the greenhouse system integrated with an objective function and an optimization algorithm. The multilayer perceptron model is trained using historical data from the greenhouse with solar radiation, outside temperature, humidity difference, fan speed, HVAC control as the input parameters to predict the temperature. …"