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通过Greylag Goose优化和机器学习,提高电动汽车的CO2排放预测

Ahmed El-Sayed Saqr1, Mohamed S Saraya2, El-Sayed M El-Kenawy3

  • 1Computer Engineering and Control Systems Department, Faculty of Engineering, Mansoura University, Mansoura, 35516, Egypt. a7mdsqr@std.mans.edu.eg.

Scientific reports
|May 13, 2025
PubMed
概括

准确的电动汽车 (EV) 排放预测对于可持续性至关重要. 与多层感知器 (MLP) 模型集成的新Greylag Goose Optimization (GGO) 显著提高了预测准确性.

关键词:
[公式:见文本]排放预测的方法电动汽车 (EV) 是一种电动汽车.灰色的优化 (GGO)多层感知器 (MLP) 是一种多层感知器.可持续的运输可持续的运输

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