Method and system for deduction and acquisition of water quality data based on machine learning

Abstract

The present application discloses a method and system for obtaining water quality data deduction based on machine learning. The method is divided into a model generation stage and a model deduction stage. In the model generation stage, the historical data of various characteristics collected by each monitoring station in the water area under study is analyzed and processed, and the independent relevant feature set of the target water quality factor and its corresponding historical data set are obtained. The machine learning method obtains the optimal derivation model of the target water quality factor; in the model derivation stage, the data of each feature factor covered by the independent relevant feature set for a certain period of time is collected, and the data is input into the optimal derivation model, and the target water quality factor of the period is calculated. The data. The present application is a new water quality data acquisition method that does not require traditional data acquisition methods such as chemical reagents and sensor detection, can reduce environmental pollution and hidden dangers caused by traditional water quality data acquisition methods, and has the advantages of low cost, safety, environmental protection and high technical added value.

Description

technical field

[0001] The present application relates to the technical fields of water quality monitoring data acquisition and data science, and in particular, to a method and system for deriving and acquiring water quality data based on machine learning. Background technique

[0002] The statements in this section merely mention the background art related to the present application and do not necessarily constitute prior art.

[0003] At present, water quality data, such as biological, chemical, hydrological and other characteristic data of sea areas, rivers, lakes and other waters, are mainly collected by sampling analysis and measurement and sensor detection. Sampling analysis, such as chemical reagents, optical methods, ion methods, etc., requires the investment of instruments, reagents and manpower, and the purchase, deployment and maintenance costs of water quality sensors are also high. Due to the wide range of water areas, the acquisition of water quality data usua...

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