بدائل البحث:
process optimization » model optimization (توسيع البحث)
search process » research process (توسيع البحث), hierarchy process (توسيع البحث)
b process » _ process (توسيع البحث), a process (توسيع البحث)
binary b » binary _ (توسيع البحث)
process optimization » model optimization (توسيع البحث)
search process » research process (توسيع البحث), hierarchy process (توسيع البحث)
b process » _ process (توسيع البحث), a process (توسيع البحث)
binary b » binary _ (توسيع البحث)
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Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19.
منشور في 2021"…P <0.05 was considered statistically significant. (B). The MCDM algorithm-Stage 2. Feature Ranking, this stage is the process of using the TOPSIS method to rank features. …"
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Table_1_bSRWPSO-FKNN: A boosted PSO with fuzzy K-nearest neighbor classifier for predicting atopic dermatitis disease.docx
منشور في 2023"…In bSRWPSO-FKNN, the core of which is to optimize the classification performance of FKNN through binary SRWPSO.…"
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Parameter settings.
منشور في 2024"…<div><p>Differential Evolution (DE) is widely recognized as a highly effective evolutionary algorithm for global optimization. It has proven its efficacy in tackling diverse problems across various fields and real-world applications. …"
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Algoritmo de clasificación de expresiones de odio por tipos en español (Algorithm for classifying hate expressions by type in Spanish)
منشور في 2024"…</li></ul><p dir="ltr"><b>File Structure</b></p><p dir="ltr">The code generates and saves:</p><ul><li>Weights of the trained model (.h5)</li><li>Configured tokenizer</li><li>Training history in CSV</li><li>Requirements file</li></ul><p dir="ltr"><b>Important Notes</b></p><ul><li>The model excludes category 2 during training</li><li>Implements transfer learning from a pre-trained model for binary hate detection</li><li>Includes early stopping callbacks to prevent overfitting</li><li>Uses class weighting to handle category imbalances</li></ul><p dir="ltr">The process of creating this algorithm is explained in the technical report located at: Blanco-Valencia, X., De Gregorio-Vicente, O., Ruiz Iniesta, A., & Said-Hung, E. (2025). …"
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Thesis-RAMIS-Figs_Slides
منشور في 2024"…<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…"