The present application relates to the field of
water quality monitoring and regulation, and particularly relates to a method for intelligent monitoring and closed-loop regulation of
water quality in feed mandarin fish factory farming. The method includes the following steps: obtaining and normalizing an
original data set,
coupling and reconstructing the normalized
original data set to generate continuous space data; generating water stratification indexes based on the continuous space data; constructing
pollution competition ratios, deviation degrees of current temperatures from
optimal growth temperatures, buffer capacity inhibition factors, and acid-base risk mapping factors based on the continuous space data, normalizing them respectively, and further constructing risk entropy; constructing behavior responses based on the continuous space data to generate behavior response values; and constructing
potential energy functions based on the behavior response values, risk entropy, and water stratification indexes to obtain regulation directions and comprehensive control output quantities. The method solves the problems of multi-
source data dispersion, discontinuous
spatial distribution, difficulty in quantifying
coupling relationships between key parameters, and lack of
biological feedback basis for regulation and decision-making.