基于模糊粗糙集和D-S证据理论的多源灌溉信息融合方法

针对多源灌溉信息决策过程中不确定性信息难以融合的问题，提出了一种基于模糊粗糙集和D-S证据理论相结合的决策融合方法。运用模糊粗糙集理论，建立基本概率分配函数，计算各灌溉因子与灌溉决策之间的依赖程度，构建多个融合灌溉因子对灌溉决策的识别框架；然后运用改进的D-S证据理论，进行多源灌溉信息决策层级的融合，最终解决不确定信息的表达和合成问题。应用上述方法对华北地区冬小麦土壤水分、光合速率和气孔导度等信息进行灌溉决策融合，结果显示：灌溉决策的不确定性由融合前的最高38%降至9.84%，该方法可有效地提高灌溉决策精度，降低灌溉决策的不确定性

Multi-source irrigation information fusion method based on fuzzy rough set and D-S evidence theory

Concerning the problem that uncertainty information is difficult to be merged during the decision-making process of multi-source irrigation information, a decision fusion method based on fuzzy rough set and Dempster-Shafer (D-S) evidence theory was proposed. Using the fuzzy rough set theory,the basic probability distribution function was established, the interdependence between irrigation factors and irrigation decision was calculated, and the identification framework of irrigation decision on the multiple fusion irrigation factors was built. Using the improved D-S evidence theory, the multi-source irrigation information was fused at the decision-making level, the expression and synthesis problems of uncertain information were solved. The information of winter wheat such as soil moisture, photosynthetic rate and stomatal conductance in north China was fused in irrigation decision by the application of the methods mentioned above. The results show that the uncertainty of the irrigation decision decreases from 38.0% before fusion to 9.84%. The method can effectively improve the accuracy of irrigation decision and reduce the uncertainty of the irrigation decision.