在反向传播神经网络下,在智能城市中分析农村振兴服务平台
Gongyi Jiang1, Weijun Gao2, Meng Xu3
1Foreign Languages Department, Tourism College of Zhejiang, Hangzhou, China.
PloS one
|March 18, 2025
概括
本研究使用灰色关系分析-反向传播神经网络 (GRA-BPNN) 来评估农村振兴旅游服务,实现高准确性. 该模式增强了农村旅游业的发展,并支持复兴工作.
科学领域:
- 应用的人工智能应用的人工智能
- 旅游管理 旅游管理
- 区域发展 区域发展
背景情况:
- 农村振兴对于经济发展和加强农村旅游业至关重要.
- 现有的模型需要复杂的方法来准确评估农村旅游服务.
- 智慧城市的前景为评估农村地区旅游服务提供了新的途径.
研究的目的:
- 开发和验证一个评估农村振兴旅游服务的模型.
- 使用灰色关系分析 (GRA) 算法对农村振兴发展进行分类.
- 评估拟议的GRA-反向传播神经网络 (GRA-BPNN) 模型的有效性.
主要方法:
- 使用逆向传播神经网络 (BPNN) 构建农村振兴发展模型.
- 使用灰色关系分析 (GRA) 算法对农村振兴工作的分类.
- 农村振兴指标的一致性测试和建立旅游服务评估模型.
主要成果:
- 在农村振兴评估中,GRA-BPNN模型表现出卓越的性能,达到92.3%的准确性.
- 一致性测试证实了旅游信息,安全,运输,环境和管理服务数据的可靠性.
- 旅游信息和管理服务主要被评为C,而运输和安全服务被评为D.
结论:
- 在评估农村振兴旅游服务方面,GRA-BPNN算法非常有效.
- 该研究提供了一种可靠的方法来评估和提高农村旅游质量.
- 优化农村振兴旅游服务平台有助于可持续的农村发展.
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