Aquaculture water quality short-time combination forecast method on basis of multi-scale analysis

Abstract

The invention discloses an aquaculture water quality short-time combination forecast method on the basis of multi-scale analysis. The method includes the steps that water quality time sequence data are acquired online and repaired; through empirical mode decomposition, the selected water quality time sequence sample set data are decomposed into IMF components and residual rn components, wherein the IMF components and the residual rn components are different in frequency scale; the IMF components and the rn components are classified, a manual bee colony optimization least square support vector regression machine, a BP neural network and an autoregressive sliding average model are respectively selected for forecast according to classifying features, and finally, all results are weighed and summed to obtain a water quality time sequence forecast result. According to the method, the original water quality time sequence data are decomposed into the components different in time frequency through the empirical mode decomposition, and change conditions in original water quality sequences can be mastered more accurately; advantages of the manual bee colony optimization least square support vector regression machine, advantages of the BP neural network and advantages of the autoregressive sliding average model are complemented and combined, and thus performance of a combined forecast model is effectively improved.

Description

technical field [0001] The invention belongs to the intersection field of intelligent information processing and aquaculture technology, and in particular relates to a short-term combination prediction method for aquaculture water quality based on multi-scale analysis. Background technique [0002] The water body of intensive aquaculture is the habitat of aquatic products, and the quality of aquaculture water directly determines the growth status and product quality of aquatic products. The water quality prediction of aquaculture is an important basic work for planning the water environment planning of the aquaculture area and the precise management of modern fishery healthy farming. Accurate water quality prediction is of great economic importance to the scientific regulation of aquaculture water quality, the prevention of water quality deterioration, and the outbreak of aquatic product diseases. value and practical significance. [0003] At present, there are mainly two t...

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Problems solved by technology

[0004] The purpose of the embodiments of the present invention is to provide a short-term combination prediction method for aquaculture water quality based on multi-scale analysis, aiming to solve the problems of low prediction accuracy and inaccuracy in existing water quality prediction methods

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