Showing 61 - 80 results of 200 for search '(( test processing algorithm ) OR ((( element data algorithm ) OR ( element based algorithm ))))', query time: 0.14s Refine Results
  1. 61

    Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm by Youssef, H.

    Published 2020
    “…In this paper, we present an approach based on Simulated Evolution algorithm for the design of SEN topology. …”
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  2. 62

    A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai by ALGHANEM, HANI SUBHI MOHD

    Published 2024
    “…The proposed framework comprises key elements: Important Decisions derived from interviews with transportation leaders, Knowledge Management enhanced by AI algorithms, Data Mining/Analysis utilizing historical data, the Fleet Management System employing Oracle ERP, and a Data-Driven Decision Support Framework that leans towards the extended framework approach. …”
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  3. 63

    Prediction the performance of multistage moving bed biological process using artificial neural network (ANN) by Fares Almomani (12585685)

    Published 2020
    “…To cope with this difficult task and perform an effective and well-controlled BP operation, an artificial neural network (ANN) algorithm was developed to simulate, model, and control a three-stage (anaerobic/anoxic and MBBR) enhanced nutrient removal biological process (ENR-BP) challenging real wastewater. …”
  4. 64
  5. 65

    Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

    Published 2025
    “…Cohesive data collections exceeding four hundred molecules under standardized test conditions deliver coefficients of determination above 0.90 and root-mean-square errors below 0.05. …”
  6. 66

    Fuzzy Logic Adaptive Crow Search Algorithm for MPPT of a Partially Shaded Photovoltaic System by Mohamed Ali Zeddini (22047920)

    Published 2024
    “…Furthermore, a higher value of the fl is preferred to guide the optimization process in the direction of global search, whilst a lower fl value directs the algorithm in the direction of local search. …”
  7. 67

    Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms by Md Ferdous Wahid (13485799)

    Published 2022
    “…This study aims to develop five robust machine learning (ML) algorithms and their fusions for a wide range of flow patterns (FP) regimes. …”
  8. 68

    Monitoring Bone Density Using Microwave Tomography of Human Legs: A Numerical Feasibility Study by Alkhodari, Mohanad Ahmed

    Published 2021
    “…This study was performed using an in-house finite-element method contrast source inversion algorithm (FEM-CSI). …”
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  9. 69

    A localized navigation algorithm for radiation evasion for nuclear facilities: Optimizing the "Radiation Evasion" criterion: Part I by Khasawneh, Mohammad

    Published 2013
    “…The proposed algorithm is tested under the “Radiation Evasion” criterion. …”
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  10. 70

    Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network by Mohammad Reza Chalak Qazani (13893261)

    Published 2024
    “…Computational techniques, like the finite element method, are used to analyse behaviours based on varied input parameters. …”
  11. 71

    Automatic image quality evaluation in digital radiography using a modified version of the IAEA radiography phantom allowing multiple detection tasks by Ioannis A. Tsalafoutas (14776939)

    Published 2025
    “…<h3>Purpose</h3><p dir="ltr">To evaluate image quality (IQ) of for‐processing (raw) and for‐presentation (clinical) radiography images, under different exposure conditions and digital image post‐processing algorithms, using a phantom that enables multiple detection tasks.…”
  12. 72

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

    Published 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. …”
  13. 73

    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
    “…The proposed algorithm has been tested on three tank system pilot plant and Ain El Kebira Cement rotary kiln process. …”
  14. 74
  15. 75

    Optimal scheduling algorithm for residential building distributed energy source systems using Levy flight and chaos-assisted artificial rabbits optimizer by D., Sathish Kumar

    Published 2023
    “…Based on the average Friedman’s ranking test values, the proposed algorithm stands first with 1.82 for numerical and real-world scheduling problems.…”
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  16. 76
  17. 77

    Optimal scheduling algorithm for residential building distributed energy source systems using Levy flight and chaos-assisted artificial rabbits optimizer by M. Premkumar (12757280)

    Published 2023
    “…Based on the average Friedman’s ranking test values, the proposed algorithm stands first with 1.82 for numerical and real-world scheduling problems. …”
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  19. 79

    A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method by Amit Kumar Balyan (18288964)

    Published 2022
    “…To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”
  20. 80

    A Hybrid Approach for Predicting Critical Machining Conditions in Titanium Alloy Slot Milling Using Feature Selection and Binary Whale Optimization Algorithm by Amirsajjad Rahmani (17541453)

    Published 2023
    “…In this study, features were extracted from signals in time, frequency, and time–frequency domains. The t-test and the binary whale optimization algorithm (BWOA) were applied to choose the best features and train the support vector machine (SVM) model with validation and training data. …”