This work investigates the functions of hardware-implemented intelligent decision support system using support vector machines. The system aims to forecast future productivity based on the data prepared by field experts followed by productivity influence factors. This feature is perceived by the combination of fuzzy logic and support vector machine. The proposed approach has been thoroughly tested at a ground level, and the designed structural test results have made major improvements compared to the lack of proper approach. This system proposed to compensate for performance decrease, achieved higher productivity with a prediction accuracy of 95%. Furthermore, the proposed intelligent embedded decision support system provided the deficit level of needed input scale to increase productivity and avoid excess consumption of fertilizer in agriculture. A 30-year climate parameter has been taken into account to establish such a system to control the consumption of fertilizers.

这项工作研究了使用支持向量机的硬件实现的智能决策支持系统的功能。该系统旨在根据现场专家准备的数据以及生产力影响因素来预测未来的生产力。模糊逻辑和支持向量机的组合可以感知到此功能。所提出的方法已经在地面上进行了全面测试，与缺乏适当方法相比，设计的结构测试结果已取得了重大改进。该系统旨在补偿性能下降，以95％的预测精度实现了更高的生产率。此外，建议的智能嵌入式决策支持系统提供了所需投入规模的赤字水平，以提高生产力并避免农业化肥的过量消费。