Rare earth ore district underground water ammonia nitrogen concentration prediction method with Gauss artificial swarm optimization

Abstract

The invention discloses a rare earth ore district underground water ammonia nitrogen concentration prediction method with Gauss artificial swarm optimization. A support vector machine is used as a rare earth ore district underground water ammonia nitrogen concentration prediction model; a Gauss artificial swarm algorithm is used for optimizing and designing a penalty factor C of the support vector machine, a radial base core parameter g and a parameter Epsilon in a non-sensitive loss function. In the Gauss artificial swarm algorithm, an outstanding individual in each individual neighborhood and an individual average value in a neighborhood thereof are merged into a Gauss mutation strategy to generate new individuals; in addition, a reverse study strategy using the optimum individuals as reference points is executed in a bee searching process. The method has the advantage that the prediction precision of the rare earth ore district underground water ammonia nitrogen concentration can be improved.

Description

Technical field [0001] The invention relates to the field of prediction of groundwater ammonia nitrogen concentration, in particular to a method for prediction of groundwater ammonia nitrogen concentration in rare earth mining areas optimized by Gaussian artificial bee colony. Background technique [0002] Rare earths play a pivotal role in the development of modern technology. Among my country's rare earth resources, the southern region is rich in ionic rare earth resources. Ionic rare earth occupies an irreplaceable position in industrial production. However, in the process of mining ionic rare earths, a large amount of ammonium sulfate and ammonium bicarbonate needs to be injected into the soil, and these ammonium sulfate and ammonium bicarbonate will gradually penetrate deep underground and pollute groundwater. In order to control the pollution of groundwater in ionic rare earth mining areas, it is necessary to grasp the dynamic changes of various indicators of groundwater....

AI Technical Summary

Problems solved by technology

[0005] Aiming at the shortcomings of the traditional artificial bee colony algorithm, which is easy to fall into local optimum and low prediction accuracy when predicting the ammonia nitrogen concentration in the groundwater of the rare earth mining area, a Gaussian artificial bee colony optimization method for the prediction of the ammonia nitrogen concentration in the groundwater of the rare earth mining area is proposed.

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