卫星遥感农业监测系统中实例检索算法研究

针对智慧农业中需求获取手段、表达方法等导致智能设计算法复杂度高、可用性低等问题，将卫星遥感技术和网络技术结合实现农作物及其生长环境参数的实时监测，以优化播种机设计的需求特征，并以此为基础，提出基于混合相似度的实例检索模型。在该模型中，设计了多级实例库结构，并以特征间距离相似度、特征间可拓关联度、特征间可拓距测度为组成要素，构造多级混合相似度的层次结构与计算方法，进行多级实例检索。将其应用到铲式播种机的数字化设计系统中，可获得与目标实例最相似的实例。实验结果表明，在实例的特征值数据类型多样化的情况下，此算法能够有效地检索出合适的历史实例，提高检索结果的可用性。

Research on Case Retrieval Algorithm in Satellite Remote Sensing Monitoring System for Agriculture

The acquisition means and expression methods of demands in intelligent agriculture result in the high complexity and low usability of the intelligent mechanic design methods. To reduce this complexity, improve the usability, and optimize the demand features of planter design, the real-time monitoring of the crops and the parameters in their growth environment is employed by combining the satellite remote-sensing technology with the network technology, and a hybrid similarity retrieval model is proposed in this paper. Moreover, to perform the multi-hierarchical case retrieval, the hierarchy and calculation methods of the algorithm are constructed in this model by integrating the distance similarity between features, the extension correlation degree between features, and the extension distance between features based on the design of the multi-hierarchy case base. The proposed method is applied to the digital design system of a spade planter and the cases most similar to the target case are obtained. The experimental results indicate that under the condition of the diverse data types of cases feature values, the proper history cases are obtained and the usability of the retrieval results is improved.