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

A technology of machine learning and acquisition methods, applied in chemical information database systems, machine learning, chemical machine learning, etc., can solve the problems of high comprehensive cost of obtaining water quality data, environmental pollution of water quality data, risk factors, etc., and achieve high-tech added value , the effect of improving the accuracy of calculation and improving the utilization rate

Active Publication Date: 2022-07-19
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the wide range of water areas, the acquisition of water quality data usually requires extensive distribution and periodic collection. At the same time, the acquisition of some water quality data also has environmental pollution and risk factors. Therefore, the comprehensive cost of obtaining water quality data has always been high.

Method used

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

Examples

Experimental program
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Effect test

Embodiment 1

[0030] This embodiment provides a method for deriving and obtaining water quality data based on machine learning;

[0031] like figure 1 and figure 2 As shown, the water quality data deduction and acquisition method based on machine learning includes: model generation stage and data deduction stage;

[0032] In the model generation stage, the machine learning method is used to generate the independent relevant feature set and the optimal deduction model of the target water quality factor;

[0033] In the data deduction stage, the data set of each water quality factor covered by the independent relevant feature set for a certain period of time is input into the optimal deduction model, and the target water quality factor data of the current period is calculated.

[0034] Further, the model generation stage includes the following steps:

[0035] S1-1: Determine the research water area E and the target water quality factor x, and obtain the water quality monitoring historical...

Embodiment 2

[0077] This embodiment provides a water quality data deduction and acquisition system based on machine learning;

[0078] A water quality data deduction and acquisition system based on machine learning, including: model generation module and data deduction module;

[0079] A model generation module, which is configured to: use a machine learning method to generate an independent relevant feature set and an optimal deduction model of the target water quality factor;

[0080] The data deduction module is configured to: input the data set of each water quality factor covered by the independent relevant feature set in a certain period of time into the optimal deduction model, and calculate the target water quality of the current period.

[0081] It should be noted here that the above-mentioned model generation module and data derivation module correspond to the model generation stage and data derivation stage in Embodiment 1, and the examples and application scenarios implemented ...

Embodiment 3

[0085] This embodiment also provides an electronic device, comprising: one or more processors, one or more memories, and one or more computer programs; wherein the processor is connected to the memory, and the one or more computer programs and The data is stored in the memory, and when the electronic device runs, the processor executes one or more computer programs stored in the memory, so that the electronic device executes the method described in the first embodiment.

[0086] It should be understood that, in this embodiment, the processor may be a central processing unit CPU, and the processor may also be other general-purpose processors, digital signal processors DSP, application-specific integrated circuits ASIC, off-the-shelf programmable gate array FPGA or other programmable logic devices , discrete gate or transistor logic devices, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor o...

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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...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G16C20/70G16C20/90G01N33/18G06N20/00
CPCG16C20/70G16C20/90G01N33/18G06N20/00
Inventor 程杰
Owner SHANDONG UNIV
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