The invention discloses an
aedes albopictus
drug resistance prediction and dynamic prevention and control
decision system and method. The method comprises the following steps: S1, acquiring multi-source spatio-temporal data of a target monitoring area; s2, on the basis of real-time meteorological data and
aedes albopictus
population characteristics, constructing an
aedes albopictus
population generation replacement deduction model, and calculating a
reproduction algebra; s3, on the basis of a
population genetics principle, constructing a
drug-resistant
gene frequency evolution model introducing fitness cost, and calculating the frequency of a resistant
allele in the current population; and S4, adopting a multi-objective optimization
algorithm based on
model predictive control, taking minimization of resistance growth and prevention and control cost and maximization of killing efficiency as objectives, performing deduction
simulation, and selecting a strategy with the highest comprehensive
score as a prevention and control method. According to the method, the resistance evolution law can be accurately quantified, the prevention and control requirements can be dynamically adapted, the problem of sharp increase of
drug resistance caused by traditional empirical prevention and control is effectively solved, the service life of the insecticide is remarkably prolonged, and accurate and low-consumption long-term sustainable prevention and control are achieved.