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Showing 201 - 220 results of 574 for search '(( element data algorithm ) OR ((( based model algorithm ) OR ( neural coding algorithm ))))', query time: 0.13s Refine Results
  1. 201
    Optimal Sizing and Techno-Economic Analysis of Hybrid Renewable Energy Systems—A Case Study of a Photovoltaic/Wind/Battery/Diesel System in Fanisau, Northern Nigeria

    Optimal Sizing and Techno-Economic Analysis of Hybrid Renewable Energy Systems—A Case Study of a Photovoltaic/Wind/Battery/Diesel System in Fanisau, Northern Nigeria by Nasser Yimen (16697129)

    Published 2020
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  2. 202
    Second-order conic programming for data envelopment analysis models

    Second-order conic programming for data envelopment analysis models by Mourad, Nahia

    Published 2022
    “…Indeed, the aforesaid method is based on mathematical optimization. This paper constructs a second-order conic optimization problem unifying several DEA models. …”
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  3. 203
    Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization

    Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization by Abu Zitar, Raed

    Published 2024
    “…The proposed simulated model can find the most relevant sensor(s) capable of generating the best quality tracks based on weighted distance criteria (Euclidean and Mahalanobis ). …”
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  4. 204
    Modeling, testing, and regression testing of web applications. (c2006)

    Modeling, testing, and regression testing of web applications. (c2006) by Al Shaar, Hamzeh K.

    Published 2006
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  5. 205
    UML-based regression testing for OO software

    UML-based regression testing for OO software by Mansour, Nashat

    Published 2010
    “…When working with large and complex object-oriented systems, source code-based regression testing is usually costly. This paper proposes a programming-language-independent technique for regression test selection for object-oriented software based on Unified Modeling Language (UML 2.0) design diagrams. …”
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  6. 206
    Iterative Methods for the Solution of a Steady State Biofilter Model

    Iterative Methods for the Solution of a Steady State Biofilter Model by Salih, Mubarak Sahal

    Published 2017
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  7. 207
    Modélisation et validation des modèles de véhicules hybrides

    Modélisation et validation des modèles de véhicules hybrides by Mansour, Charbel

    Published 2009
    “…Ensuite, une analyse approfondie du GMP série/parallèle est réalisée: étude de cas de la Prius. Un modèle et une validation expérimentale du GMP Toyota Hybrid System (THS-II) sont élaborés. …”
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  8. 208
    Improving Rule Set Based Software Quality Prediction

    Improving Rule Set Based Software Quality Prediction by Azar, Danielle

    Published 2003
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  9. 209
    Automatic and Intelligent Stressor Identification Based on Photoplethysmography Analysis

    Automatic and Intelligent Stressor Identification Based on Photoplethysmography Analysis by Sami Elzeiny (16891521)

    Published 2021
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  10. 210
    Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications

    Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications by Estahbanati, Shahabeddin Vamegh

    Published 2017
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  11. 211
    Blockchain-Based Decentralized Architecture for Software Version Control

    Blockchain-Based Decentralized Architecture for Software Version Control by Muhammad Hammad (17541570)

    Published 2023
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  12. 212
    Reinforcement Learning-Based School Energy Management System

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

    Published 2020
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  13. 213
    Information reconciliation through agent controlled graph model. (c2018)

    Information reconciliation through agent controlled graph model. (c2018) by Saba, Rita

    Published 2018
    “…Our approach provides a damage assessment and recovery algorithm that is based on agents and graphs.…”
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  14. 214
    A Novel Centrality-Based Approach for Link Prediction

    A Novel Centrality-Based Approach for Link Prediction by El Khoury, Elissa Lichaa

    Published 2025
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  15. 215
    Variable Selection in Data Analysis: A Synthetic Data Toolkit

    Variable Selection in Data Analysis: A Synthetic Data Toolkit by Mitra, Rohan

    Published 2024
    “…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …”
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  16. 216
    Reinforcement R-learning model for time scheduling of on-demand fog placement

    Reinforcement R-learning model for time scheduling of on-demand fog placement by Farhat, Peter

    Published 2020
    “…Therefore, there is a need for an intelligent model capable of scheduling fog placement based on the user’s requests. …”
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  17. 217
    Internal Model Control Structure Using Adaptive Inverse Control Strategy

    Internal Model Control Structure Using Adaptive Inverse Control Strategy by Shafiq, M.Riyaz

    Published 2003
    “…The internal model of the plant is estimated by recursive least square algorithm and the inverse of the system by least mean square. …”
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  18. 218
    Cooperative clustering models for Vehicular ad hoc networks. (c2013)

    Cooperative clustering models for Vehicular ad hoc networks. (c2013) by Abdel Wahab, Omar Mohammad

    Published 2013
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  19. 219
    Machine Learning-Based Approach for EV Charging Behavior

    Machine Learning-Based Approach for EV Charging Behavior by Shahriar, Sakib

    Published 2021
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  20. 220
    Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval

    Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval by Mohammed Tahar Habib Kaib (21633176)

    Published 2024
    “…Generally, RKPCA reduces the number of samples in the training data set and then builds the KPCA model based on this data set. In this paper, the proposed algorithm selects relevant observations from the original data set by utilizing a class interval technique (i.e. histogram) to maintain a bunch of representative samples from each bin. …”
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