The invention relates to an intelligent
algorithm recommendation method and
system for pet personalized prescription food. The method comprises the following steps: acquiring physiological information of a pet, and analyzing the physiological information to obtain a specific physiological demand vector; then, combining the demand vector with a nutriology standard
database, and calculating to obtain a
nutrition proportioning scheme; then, deviation analysis is carried out on the recent diet
record and health feedback data of the pet according to the
nutrition proportioning scheme, adjustment demand parameters are obtained, and when the adjustment demand parameters exceed a preset threshold value, iterative optimization is carried out on the
nutrition proportioning scheme to obtain
personalized nutrition proportioning; screening
food material combinations according to the
personalized nutrition ratio to obtain a prescription food formula recommendation
list for each pet; and finally, based on the prescription grain formula recommendation
list and the physiological data after
ingestion, generating a new prescription grain formula recommendation
list. The pet nutrition scheme can be planned in advance, and nutrition balance of pets in different growth stages and
health states can be guaranteed comprehensively.