The invention relates to an improved reinforced immune
algorithm-based agricultural internet-of-things
resource allocation method. Related information of resource demand points and supply points in
agriculture is obtained by adopting an internet-of-things technology, and the supply points perform efficient
resource allocation on the demand points through allocation vehicles by utilizing an improved reinforced immune
algorithm; and the improved reinforced immune
algorithm is an algorithm obtained after an immune algorithm is improved by utilizing a
reinforcement learning thought, the improvement refers to the initialization of a Q table according to the distances between the
resource supply points and demand points where the vehicles are located, the Q table is updated according to an
antibody with a minimum fitness value currently in each iteration,
mutation of the
antibody is guided by using the current Q table in a
mutation stage, and meanwhile, when the Q table is continuously updated in the same position, the Q table is adjusted to escape from
local optimum. The method has the characteristics of strong learning capability, high self-adaptivity, numerous allocation objects and high response speed.