在特伦蒂诺葡萄园中使用模糊决策支持系统进行智能灌
Romeo Silvestri1, Massimo Vecchio1, Miguel Pincheira1
1Fondazione Bruno Kessler, 38122 Trento, Italy.
Sensors (Basel, Switzerland)
|December 11, 2025
概括
本研究比较了葡萄园的两个模糊逻辑灌系统. 马姆丹尼系统使用专家规则,而塔卡吉-苏格诺系统从现场数据中学习,提供了对节水和作物压力管理的见解.
科学领域:
- 农业工程 农业工程
- 环境科学 环境科学
- 计算机科学 计算机科学
背景情况:
- 由于气候变化和水资源短缺,高效的水资源管理对农业至关重要.
- 葡萄园灌需要复杂的决策支持系统来优化用水.
研究的目的:
- 为葡萄园管理进行两种模糊逻辑灌决策支持系统 (Mamdani和Takagi-Sugeno) 的实地比较评估.
- 评估这些系统在用水效率,土壤湿度控制和强度方面的性能.
主要方法:
- 基于Mamdani类型和Takagi-Sugeno模糊逻辑控制器的现场评估.
- 集成土壤湿度传感,短期预报和天气预报.
- 针对绩效评估的反事实模拟和基于引导的统计分析.
主要成果:
- 这两种模糊逻辑系统都提供了优化的灌建议.
- 在Mamdani (专家规则) 和Takagi-Sugeno (自动学习) 方法之间确定了明显的优势和权衡.
- 这项研究揭示了在节水和减轻作物压力方面的不同表现.
结论:
- 该比较评估为设计和部署农业中智能灌管理解决方案提供了实际见解.
- 在Mamdani和Takagi-Sugeno系统之间做出选择取决于有关节水和作物健康的具体管理目标.
- 模糊逻辑控制器在可变的环境条件下,有望提高葡萄园的用水效率.
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