Wu, Y., Cai, X., & Zhang, Z. (2026). Evaluation and Optimization of the Effectiveness of Science Popularization Resources Using a Multi-Model Machine Learning Approach Combining Entropy Weight, XGBoost, and SHAP. 2026 International Conference on Computational Intelligence and Machine Learning (CIML), Computational Intelligence and Machine Learning (CIML), 2026 International Conference on, 596. https://doi.org/10.1109/CIML69155.2026.11692634
Παραπομπή σε μορφή Chicago (17η εκδ.)Wu, Yuju, Xiaoying Cai, και Zhe Zhang. "Evaluation and Optimization of the Effectiveness of Science Popularization Resources Using a Multi-Model Machine Learning Approach Combining Entropy Weight, XGBoost, and SHAP." 2026 International Conference on Computational Intelligence and Machine Learning (CIML), Computational Intelligence and Machine Learning (CIML), 2026 International Conference on 2026: 596. https://doi.org/10.1109/CIML69155.2026.11692634.
Παραπομπή σε μορφή MLA (9th εκδ.)Wu, Yuju, et al. "Evaluation and Optimization of the Effectiveness of Science Popularization Resources Using a Multi-Model Machine Learning Approach Combining Entropy Weight, XGBoost, and SHAP." 2026 International Conference on Computational Intelligence and Machine Learning (CIML), Computational Intelligence and Machine Learning (CIML), 2026 International Conference on, 2026, p. 596, https://doi.org/10.1109/CIML69155.2026.11692634.