Prediction of weed dispersal dynamics: determining multiple concurrent fuzzy consequences using priority stacks on a blackboard model

This paper details the framework and methodology of how weed dispersal dynamics can be predicted using concurrent fuzzy if-then rules applied to spatial datasets. This involves multiple fuzzy rules that are employed simultaneously to infer multiple factors that can influence the predicted outcome. To determine which DOF (degree-of-fulfilment) to accept as the final consequent, a priority stack is used based on a blackboard model. This technique is applied to spatial datasets displaying the predicted outcome of weed distribution.