Kazan (Volga region) Federal University, KFU
KAZAN
FEDERAL UNIVERSITY
 
EMPLOYEE PERFORMANCE PREDICTION: AN INTEGRATED APPROACH OF HYBRID IMPROVED LA-CNN-SVM-BILSTM MODEL
Form of presentationArticles in international journals and collections
Year of publication2024
Языкрусский
  • Salimzyanova Elmira Shavkatovna, author
  • Bibliographic description in the original language S. Donthu, E. S. Salimzyanova, A. Hashmi, N. L. Mishra, J. M. Johnson and A. S. Employee Performance Prediction: An Integrated Approach of Hybrid Improved LA-CNN-SVM-BiLSTM Model // 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS), Hassan, India, 2024. - pp. 1-6, doi: 10.1109/IACIS61494.2024.10721887.
    Annotation 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS), Hassan, India, 2024
    Keywords Support vector machines; Productivity; Training; Accuracy; Reviews; Computational modeling; Companies; Predictive models; Feature extraction; Vectors; employees? performance; convolutional neural network (CNN); support vector machine (SVM)
    The name of the journal 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS), Hassan, India, 2024
    URL https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10721887
    Please use this ID to quote from or refer to the card https://repository.kpfu.ru/eng/?p_id=306172&p_lang=2

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