Showing 81 - 100 results of 471 for search '(((( develop robust algorithm ) OR ( relevant data algorithm ))) OR ( data models algorithm ))', query time: 0.12s Refine Results
  1. 81
  2. 82

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

    Published 2018
    “…Multiple models have been proposed and different techniques and data structures were used. …”
    Get full text
    Get full text
    Get full text
    masterThesis
  3. 83
  4. 84
  5. 85
  6. 86

    C-3PA: Streaming Conformance, Confidence and Completeness in Prefix-Alignments by Raun, Kristo

    Published 2023
    “…The aim of streaming conformance checking is to find dis crepancies between process executions on streaming data and the refer ence process model. The state-of-the-art output from streaming confor mance checking is a prefix-alignment. …”
    Get full text
    Get full text
    Get full text
  7. 87

    A depth-controlled and energy-efficient routing protocol for underwater wireless sensor networks by Umesh Kumar Lilhore (17727684)

    Published 2022
    “…The proposed energy-efficient routing protocol is based on an enhanced genetic algorithm and data fusion technique. In the proposed energy-efficient routing protocol, an existing genetic algorithm is enhanced by adding an encoding strategy, a crossover procedure, and an improved mutation operation that helps determine the nodes. …”
  8. 88
  9. 89
  10. 90

    Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy by Haitao Xu (435549)

    Published 2023
    “…Adjusting the weight and bias of the ANN model using an optimization algorithm is known as the training process. …”
  11. 91
  12. 92
  13. 93

    Four quadrant robust quick response optimally efficient inverterfed induction motor drive by Islam, S.M.

    Published 1989
    “…The control algorithms developed are readily implementable with present-day microprocessors…”
    Get full text
    Get full text
    article
  14. 94

    Predict Student Success and Performance factors by analyzing educational data using data mining techniques by ATIF, MUHAMMAD

    Published 2022
    “…The model is then applied to data collected from a reputable university that included 126,698 records with twenty-six (26) initial data attributes. …”
    Get full text
  15. 95

    Artificial Intelligence for the Prediction and Early Diagnosis of Pancreatic Cancer: Scoping Review by Zainab Jan (17306614)

    Published 2023
    “…Artificial intelligence (AI) provides advanced models and algorithms for better diagnosis of pancreatic cancer. …”
  16. 96

    Label dependency modeling in Multi-Label Naïve Bayes through input space expansion by PKA Chitra (21749216)

    Published 2024
    “…To accommodate the heterogeneity of the expanded input space, we refine the likelihood parameters of iMLNB using a joint density function, which is adept at handling the amalgamation of data types. We subject our enhanced iMLNB model to a rigorous empirical evaluation, utilizing six benchmark datasets. …”
  17. 97
  18. 98

    Privacy-Preserving Fog Aggregation of Smart Grid Data Using Dynamic Differentially-Private Data Perturbation by Fawaz Kserawi (16904859)

    Published 2022
    “…We describe our differentially-private model with flexible constraints and a dynamic window algorithm to maintain the privacy-budget loss in infinitely generated time-series data. …”
  19. 99

    Convergence of Photovoltaic Power Forecasting and Deep Learning: State-of-Art Review by Mohamed Massaoudi (16888710)

    Published 2021
    “…With the massive smart meter integration, DL takes advantage of the large-scale and multi-source data representations to achieve a spectacular performance and high PV forecastability potential compared to classical models. …”
  20. 100

    Oversampling techniques for imbalanced data in regression by Samir Brahim Belhaouari (9427347)

    Published 2024
    “…For tabular data we conducted a comprehensive experiment using various models trained on both augmented and non-augmented datasets, followed by performance comparisons on test data. …”