基于BP神经网络模型的共享雨伞需求预测探究

梅 喻, 华茹 赵, 芝怡 廖, 心海 刘, 语琳 宋

摘要


共享雨伞需求预测是一种有实际应用意义的问题，可以帮助共享雨伞服务提供商优化资源分配和提升用户体验。本研究旨在探究基于BP神经网络模型的共享雨伞需求预测方法。首先，收集了共享雨伞的历史数据，包括雨伞的借用数量、时间、地点和天气情况等。将数据集划分为训练集、验证集和测试集，用于模型训练、验证和评估。构建BP神经网络模型，并通过反向传播算法对模型进行训练和优化。最后当模型表现良好时，可将其部署到实际应用中，用于预测未来共享雨伞的需求情况。本研究为共享雨伞服务提供商提供了一种有效的需求预测方法，有助于优化运营策略和提高服务质量。

关键词


BP神经网络，共享雨伞，需求预测

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参考


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DOI: https://doi.org/10.12238/jpm.v4i8.6181

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