The application discloses an
African swine fever full-chain multi-link risk early warning method based on TAER-TCN, and belongs to the field of
animal disease prevention and control and intelligent
food safety monitoring. The method integrates full-
link data of pork circulation, constructs an integrated
risk control system, takes a time attention-error recursive time
convolution network as a core, extracts long
time sequence features, strengthens key risk information, suppresses prediction errors, and improves complex scene early warning accuracy. Relying on an asymmetric causal kernel function, the method analyzes risk cross-link transmission paths, completes risk
traceability positioning, realizes four-level graded early warning according to a
risk index, and matches corresponding disposal schemes. The application solves problems of traditional technology link fragmentation, early warning
lag, data island,
traceability difficulty, false and missed report rate and the like, has advantages of full-chain coverage,
early prediction, high precision, easy deployment and the like, is suitable for pig slaughtering,
cold chain transportation,
processing and storage and market sales scenes, and provides intelligent
technical support for pig industry safety and food
disease prevention and control.