The application discloses a city annual
water consumption prediction method based on variable point detection and segmented double-layer fusion, relates to the technical field of city
water consumption prediction, and comprises the following steps: collecting city
water consumption historical data and preprocessing to obtain annual water consumption data; calculating a water consumption growth rate sequence of adjacent years, searching for an optimal
abnormality sub-section in combination with an abnormal section length range, and identifying a water consumption
time sequence variable point section; a plurality of prediction model sets are constructed; one-step prediction is performed through rolling, prediction errors of normal sections and variable point sections are respectively counted, and two types of global fusion weights are generated; dynamic weights are solved in combination with a k-year rolling error cache and an
exponential weighting mechanism, and double-layer weights are fused; whether the target year is in a variable point section or not, parameters are adaptively adjusted, corresponding weights are matched, city water consumption final prediction results are weighted and calculated, and output. The application still has good accuracy and robustness in the variable point section.