Search alternatives:
testing algorithm » cosine algorithm (Expand Search)
method algorithm » mould algorithm (Expand Search)
data scheduling » task scheduling (Expand Search), ahead scheduling (Expand Search)
data testing » data using (Expand Search)
Showing 81 - 100 results of 263 for search '(( elements method algorithm ) OR ((( data scheduling algorithm ) OR ( data testing algorithm ))))', query time: 0.15s Refine Results
  1. 81

    Data mining approach to predict student's selection of program majors by SIDDARTHA, SHARMILA

    Published 2019
    “…The approach includes a methodology to manage data mining projects, sampling techniques to handle imbalanced data and multiclass data, a set of classification algorithms to predict and measures to evaluate performance of models. …”
    Get full text
  2. 82
  3. 83

    Evolutionary algorithms for state justification in sequential automatic test pattern generation by El-Maleh, Aiman H.

    Published 2005
    “…A common search operation in sequential Automatic Test Pattern Generation is to justify a desired state assignment on the sequential elements. State justification using deterministic algorithms is a difficult problem and is prone to many backtracks, which can lead to high execution times. …”
    Get full text
    article
  4. 84

    Novel Peak Detection Algorithms for Pileup Minimization in Gamma Ray Spectroscopy by Raad, M.W.

    Published 2006
    “…The classification technique has the unique feature of cutting down the computation largely by only allowing the event of interest to be executed by a particular algorithm. The set-up was also tested with random signals from a 137Cs test source. …”
    Get full text
    Get full text
    article
  5. 85

    An image processing and genetic algorithm-based approach for the detection of melanoma in patients by Tokajian, Sima

    Published 2018
    “…The second phase classifies lesions using a Genetic Algorithm. Our technique shows a significant improvement over other well-known algorithms and proves to be more stable on both training and testing data.…”
    Get full text
    Get full text
    Get full text
    Get full text
    article
  6. 86
  7. 87

    A method for optimizing test bus assignment and sizing for system-on-a-chip by Harmanani, Haidar M.

    Published 2017
    “…We present experimental results that demonstrate the effectiveness of our method while outperforming reported techniques.…”
    Get full text
    Get full text
    Get full text
    Get full text
    conferenceObject
  8. 88

    Assessment of static pile design methods and non-linear analysis of pile driving by Abou-Jaoude, Grace G.

    Published 2006
    “…The pile/soil interaction system is described by a mass/spring/dashpot system where the properties of each component are derived from rigorous analytical solutions or finite element analysis. The outcome of this research is an algorithm that can be used to predict pile displacement and driving stresses. …”
    Get full text
    Get full text
    Get full text
    masterThesis
  9. 89

    Application of Machine Learning Algorithms to Enhance Money Laundering and Financial Crime Detection by HAMDALLAH, KHALID WAJIH TURKI

    Published 2011
    “…The data was used as training and testing sets to analyze certain machine learning algorithms in terms of performance (cost / benefit analysis) and accuracy (mean error square and confusion matrix). …”
    Get full text
  10. 90
  11. 91

    A New Hamiltonian Semi-Analytical Approach to Vibration Analysis of Piezoelectric Multi-Layered Plates by Andrianarison, O.

    Published 2024
    “…The whole piezoelectric multilayered plate’s dynamic stiffness is then built, from which its circular frequencies are computed with the help of the Wittrick-Williams algorithm. A detailed discussion is provided on the implementation aspects, followed by some numerical examples to assess the robustness, accuracy and effectiveness of the proposed method. …”
    Get full text
    article
  12. 92
  13. 93

    Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test by Hasan T. Abbas (8115014)

    Published 2019
    “…In this paper, we present an automatic tool that uses machine learning techniques to predict the development of type 2 diabetes mellitus (T2DM). Data generated from an oral glucose tolerance test (OGTT) was used to develop a predictive model based on the support vector machine (SVM). …”
  14. 94

    The Relation Between Respiratory & Acute Coronary Syndrome Using Data Mining Techniques by DOULEH, HANI ABDULLAH YOSEF ABU

    Published 2018
    “…In healthcare world, data science is one of the most important sciences that helps in predicting diseases, and despite the availability of medical data from laboratory tests, most medical institutions in middle east region still do not benefit from these data in diseases analysis and prediction. …”
    Get full text
  15. 95
  16. 96

    Joint energy-distortion aware algorithms for cooperative video streaming over LTE networks by Yaacoub, Elias

    Published 2013
    “…The cluster heads receive the data on the long-range LTE links, either via unicasting or multicasting. …”
    Get full text
    Get full text
    Get full text
    article
  17. 97

    Prediction of EV Charging Behavior Using Machine Learning by Shahriar, Sakib

    Published 2021
    “…Using data-driven tools and machine learning algorithms to learn the EV charging behavior can improve scheduling algorithms. …”
    Get full text
    article
  18. 98

    Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology by Senyuk, Mihail

    Published 2023
    “…Features of transmission line maintenance were used to increase accuracy of estimation. Algorithms were tested using the test power system IEEE39. …”
    Get full text
    article
  19. 99

    KNNOR: An oversampling technique for imbalanced datasets by Ashhadul Islam (16869981)

    Published 2021
    “…The proposed method is compared with the ten top performing contemporary oversamplers by testing the accuracy of classifiers trained on augmented data provided by each oversampler. …”
  20. 100