CN117171660B

CN117171660B - Microorganism repair state monitoring method and system based on support vector machine

Info

Publication number: CN117171660B
Application number: CN202311445711.5A
Authority: CN
Inventors: 郭丽莉; 李书鹏; 王蓓丽; 刘亚茹; 宋倩; 李丽杰
Original assignee: BCEG Environmental Remediation Co Ltd
Current assignee: BCEG Environmental Remediation Co Ltd
Priority date: 2023-11-02
Filing date: 2023-11-02
Publication date: 2024-03-12
Anticipated expiration: 2043-11-02
Also published as: CN117171660A

Abstract

The invention relates to the field of resource environment, and discloses a microorganism repair state monitoring method, which comprises the following steps: identifying soil data and water quality data in the ecological data; classifying the soil data to obtain microorganism component data and pollution metal data, analyzing the degradation rate of the soil by utilizing the pollution metal data, analyzing the accumulation level of the soil by utilizing the microorganism component data, and analyzing the soil quality restoration level of the soil according to the degradation rate and the accumulation level; analyzing the eutrophication degree of the water body of the water quality, and acquiring the historical eutrophication degree so as to analyze the water quality change level of the water quality; calculating the inhibition level of the water planting components on the harmful substances and the growth level of the harmful substances in the water quality data, and dividing the improvement level of the water planting components according to the inhibition level and the growth level; and analyzing the water quality restoration level of the microorganism to the water quality according to the water quality change level and the improvement level so as to analyze the restoration state of the microorganism and take the restoration state as a monitoring result. The invention can accurately monitor the repair state of microorganisms.

Description

Microorganism repair state monitoring method and system based on support vector machine

Technical Field

The invention relates to the field of resource environment, in particular to a method and a system for monitoring a microbial repair state based on a support vector machine.

Background

Microbial repair status monitoring refers to the process of monitoring and assessing the ability of microorganisms to degrade and repair environmental pollutants.

At present, the monitoring of the repair state of microorganisms is generally based on a method for collecting and analyzing a microbial sample, and the repair state of the microorganisms is analyzed by identifying the change of the microorganisms during observation through a chemical method and a physical method, however, the influence of environmental change factors is ignored through the method, so that the result of monitoring the repair state of the microorganisms is not accurate enough.

Disclosure of Invention

In order to solve the technical problems, the invention provides a method and a system for monitoring the repairing state of microorganisms based on a support vector machine, which can accurately monitor the repairing state of microorganisms.

In a first aspect, the present invention provides a method for monitoring a microbial repair state based on a support vector machine, including:

extracting ecological data of a microorganism repairing area, and inputting the ecological data into a pre-constructed support vector machine so as to identify soil data and water quality data in the ecological data by using the support vector machine;

The soil data are subjected to soil classification by utilizing a data classification module in the support vector machine, so as to obtain classified soil data, wherein the classified soil data comprise microorganism component data and pollution metal data, the degradation rate of soil corresponding to the classified soil data is calculated by utilizing the pollution metal data, the accumulation level of the soil is identified by utilizing the microorganism component data, and the soil restoration level of microorganisms corresponding to the microorganism component data to the soil is analyzed according to the degradation rate and the accumulation level;

analyzing the water eutrophication degree of the water quality corresponding to the water quality data by utilizing a water quality analysis module in the support vector machine, acquiring the historical water eutrophication degree of the water quality, and analyzing the water quality change level of the water quality based on the water eutrophication degree and the historical water eutrophication degree;

identifying water planting components and harmful substances in the water quality data, inquiring the growth level of the harmful substances, calculating the inhibition level of the water planting components on the harmful substances, and analyzing the improvement level of the water planting components according to the inhibition level and the growth level;

Analyzing the water quality restoration level of the microorganism to the water quality according to the water quality change level and the improvement level, analyzing the restoration state of the microorganism according to the soil quality restoration level and the water quality restoration level, and taking the restoration state as a restoration state monitoring result of the microorganism.

In one possible implementation manner of the first aspect, the calculating, using the contaminated metal data, a degradation rate of soil corresponding to the classified soil data includes:

inquiring the historical pollution concentration and the current pollution concentration of the pollution metal data;

calculating the degradation rate of the soil according to the historical pollution concentration and the current pollution concentration by using the following formula:

；

wherein,represents degradation rate(s)>Indicating the current contamination concentration, +.>Representing the historical contamination concentration.

In one possible implementation manner of the first aspect, the analyzing a soil quality restoration level of the soil by the microorganism corresponding to the microorganism component data according to the degradation rate and the accumulation level includes:

identifying the degree of change of the active enzyme of the soil according to the degradation rate, and identifying the degree of change of the acid-base value of the soil according to the accumulation level;

And analyzing the soil quality restoration level of the microorganisms corresponding to the microorganism component data on the basis of the change degree of the active enzyme and the change degree of the acid-base value.

In one possible implementation manner of the first aspect, the analyzing, by using a water quality analysis module in the support vector machine, a water body eutrophication degree of water quality corresponding to the water quality data includes:

generating sample data of the water quality data by using the water quality analysis module;

calculating the water eutrophication rating of the water quality corresponding to the water quality data by utilizing the sample data and combining the following formula:

；

wherein,water eutrophication rating, n represents the total sample amount of the sample data, < >>Normalized weight value representing the ith data in the sample data, +.>Represents the ith sample data, +.>Represents the general index of water eutrophication evaluation,

and determining the water eutrophication degree of the water quality corresponding to the water quality data based on the water eutrophication rating.

In one possible implementation manner of the first aspect, the querying the growth level of the harmful substance includes:

creating ecological parameters of the harmful substances corresponding to the ecological environment;

inputting the ecological parameters and the harmful parameters corresponding to the harmful substances into a pre-constructed growth analysis model;

To analyze the growth level of the hazardous substance in combination with the ecological parameter and the hazardous parameter using the growth analysis model.

In one possible implementation manner of the first aspect, the calculating the inhibition level of the water planting component on the harmful substance includes:

identifying effective water planting in the water planting components, and calculating the contribution rate of the effective water planting to the inhibition of the harmful substances by using the following formula:

；

wherein,representing contribution rate->Indicating the number of active water plants, +.>Indicates the quantity of the effective water plants which can inhibit harmful substances>Represents the i-th effective water planting, +.>Indicate->Weight value of effective water planting, < ->Indicating the level inhibition factor of effective water planting on harmful substances, < >>Representing the actual inhibition coefficient of the effective water planting against harmful substances, < >>Represents the j-th hazardous substance;

calculating the decomposition rate of the water planting component to the harmful substances by using the contribution rate, and identifying the inhibition level of the water planting component to the harmful substances based on the decomposition rate.

In one possible implementation manner of the first aspect, the analyzing the water quality restoration level of the water quality by the microorganism according to the water quality change level and the improvement level includes:

Constructing a water quality change curve corresponding to the water quality change level and a water quality improvement curve corresponding to the improvement level;

performing difference calculation by using the water quality change curve and the water quality improvement curve to obtain a difference curve; calculating the curve slope of the difference curve, and analyzing the water quality restoration level of the microorganism to the water quality according to the curve slope.

In a possible implementation manner of the first aspect, the analyzing the repair status of the microorganism according to the soil repair level and the water quality repair level includes:

calculating the monitoring time of the repair area corresponding to the microorganism, and inquiring the initial monitoring state of the repair area;

and analyzing the restoration state of the microorganism according to the monitoring time, the initial monitoring state, the soil restoration level and the water restoration level.

In a possible implementation manner of the first aspect, the analyzing the repair status of the microorganism according to the monitoring time, the initial monitoring status, the soil repair level, and the water repair level includes:

performing vector conversion on the initial monitoring state to obtain an initial monitoring vector, and performing vector conversion on the soil quality restoration level and the water quality restoration level to obtain a soil quality restoration vector and a water quality restoration vector;

According to the monitoring time, the monitoring vector, the soil quality restoration vector and the water quality restoration vector, calculating a current monitoring vector corresponding to the initial monitoring vector by using the following steps:

；

wherein,representing the current monitoring vector,/-, and>representing a monitoring vector->Representing a soil repair vector,/->Representing a water quality restoration vector->Representing a monitoring time;

and calculating the difference value between the monitoring vector and the current monitoring vector to obtain a vector difference value, and carrying out inverse conversion on the vector difference value by utilizing the vector conversion relation of the initial monitoring state to obtain the repairing state of the microorganism.

In a second aspect, the present invention provides a system for monitoring the state of microbial repair based on a support vector machine, the system comprising:

the ecological data identification module is used for extracting ecological data of the microorganism restoration area, and inputting the ecological data into a pre-constructed support vector machine so as to identify soil data and water quality data in the ecological data by utilizing the support vector machine;

the soil quality restoration analysis module is used for classifying the soil data by utilizing the data classification module in the support vector machine to obtain classified soil data, wherein the classified soil data comprises microorganism component data and pollution metal data, the degradation rate of the soil corresponding to the classified soil data is calculated by utilizing the pollution metal data, the accumulation level of the soil is identified by utilizing the microorganism component data, and the soil quality restoration level of the soil by microorganisms corresponding to the microorganism component data is analyzed according to the degradation rate and the accumulation level;

The water quality change analysis module is used for analyzing the water body eutrophication degree of the water quality corresponding to the water quality data by utilizing the water quality analysis module in the support vector machine, acquiring the historical water body eutrophication degree of the water quality, and analyzing the water quality change level of the water quality based on the water body eutrophication degree and the historical water body eutrophication degree;

the water planting improvement analysis module is used for identifying water planting components and harmful substances in the water quality data, inquiring the growth level of the harmful substances, calculating the inhibition level of the water planting components on the harmful substances, and analyzing the improvement level of the water planting components according to the inhibition level and the growth level;

and the repair state monitoring module is used for analyzing the wastewater content of the production wastewater, carrying out parameter second adjustment on the first adjustment parameter based on the wastewater content to obtain a second adjustment parameter, and completing wastewater recovery of the production wastewater by using the second adjustment parameter to obtain a wastewater recovery result.

In a third aspect, the present invention provides an electronic device comprising:

at least one processor; and a memory communicatively coupled to the at least one processor;

Wherein the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the support vector machine-based microorganism repair status monitoring method of any one of the first aspects above.

In a fourth aspect, the present invention provides a computer readable storage medium storing a computer program which, when executed by a processor, implements the support vector machine-based microorganism repair status monitoring method according to any one of the first aspects.

Compared with the prior art, the technical principle and beneficial effect of this scheme lie in:

according to the scheme, the basic information of the area environment can be known by extracting the ecological data of the microorganism repair area, and the soil data is classified by utilizing the data classification module in the support vector machine, so that a large amount of disordered data can be classified into a small amount of similar aggregates by obtaining classified soil data, and the data processing efficiency can be improved; secondly, according to the embodiment of the invention, the pollution metal data are utilized to calculate the degradation rate of soil corresponding to the classified soil data, so that the metal pollution removal effect can be known; further, the embodiment of the invention can further understand the capability of microorganisms to degrade heavy metals in soil by utilizing the accumulation level of the soil through the microbial component data, and can understand the current polluted degree of the water body through analyzing the water body eutrophication degree of the water quality corresponding to the water quality data by utilizing the water quality analysis module in the support vector machine to combine the water quality data, wherein the water body eutrophication degree refers to the water body pollution caused by overnutrition in the water body; and identifying the water planting components and harmful substances in the water quality data to know the growth capacity of the harmful substances in the current environment, so as to provide reliable reference data for analyzing the restoration capacity of the water planting, and analyzing the restoration level of the microorganism to the water quality according to the water quality change level and the improvement level to know the restoration degree of the microorganism to water which is an important component in ecology in a certain period, so as to provide important analysis data for observing the state of the microorganism to ecological restoration. Therefore, the method for monitoring the microbial repair state based on the support vector machine provided by the embodiment of the invention can accurately monitor the repair state of the microorganism.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.

In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, and it will be obvious to a person skilled in the art that other drawings can be obtained from these drawings without inventive effort.

FIG. 1 is a schematic flow chart of a method for monitoring a microbial repair state based on a support vector machine according to an embodiment of the present invention;

FIG. 2 is a schematic block diagram of a system for monitoring a state of repairing microorganisms based on a support vector machine according to an embodiment of the present invention;

fig. 3 is a schematic diagram of an internal structure of an electronic device for implementing a method for monitoring a microbial repair state based on a support vector machine according to an embodiment of the present invention.

Detailed Description

It should be understood that the detailed description is presented by way of example only and is not intended to limit the invention.

The embodiment of the invention provides a microbial remediation state monitoring method based on a support vector machine, and an execution subject of the microbial remediation state monitoring method based on the support vector machine comprises, but is not limited to, at least one of a server, a terminal and the like which can be configured to execute the method provided by the embodiment of the invention. In other words, the method for monitoring the microbial repair state based on the support vector machine may be performed by software or hardware installed in a terminal device or a server device, where the software may be a blockchain platform. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like. The server may be an independent server, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.

Referring to fig. 1, a flow chart of a method for monitoring a microbial repair state based on a support vector machine according to an embodiment of the invention is shown. The method for monitoring the microbial repair state based on the support vector machine depicted in fig. 1 comprises the following steps S1-S5:

s1, extracting ecological data of a microorganism repairing area, and inputting the ecological data into a pre-constructed support vector machine so as to identify soil data and water quality data in the ecological data by using the support vector machine.

According to the embodiment of the invention, the basic information of the area environment can be known by extracting the ecological data of the microorganism restoration area, wherein the ecological data refers to the data for recording and describing various information of a natural ecological system, the data are very important for knowing and monitoring aspects such as biological diversity, environmental change, species distribution and interaction, such as species data, habitat data, functional data and the like, and the microorganism restoration area refers to the ecological environment area where the microorganism is located.

Optionally, the ecological data of the microorganism repair area is acquired through a big data system.

Furthermore, the embodiment of the invention can use microorganisms as key data of ecological restoration by utilizing the support vector machine to identify soil data and water quality data in the ecological data. The soil data refer to various parameters and indexes obtained by testing and measuring the soil, such as the ph value, the soil structure, the soil pollution degree and the like of the soil, and the water quality data refer to various parameters and indexes obtained by testing and measuring the water body, such as the temperature, the ph value, the chlorophyll content and the like of the water body.

Optionally, the identifying soil data and water quality data in the ecological data by using the support vector machine maps a preconfigured ecological training data set into a high-dimensional feature space, the support vector machine searches a hyperplane in the high-dimensional feature space, sample points of the ecological training data set can be obtained in the process of searching the hyperplane by using the support vector machine, the sample distance between the sample points and the hyperplane is calculated, and a data class is identified based on the sample distance, wherein the hyperplane is a line in a two-dimensional case, and is a plane in the high-dimensional space.

S2, classifying the soil data by utilizing a data classification module in the support vector machine to obtain classified soil data, wherein the classified soil data comprises microorganism component data and pollution metal data, calculating the degradation rate of soil corresponding to the classified soil data by utilizing the pollution metal data, identifying the accumulation level of the soil by utilizing the microorganism component data, and analyzing the soil restoration level of microorganisms corresponding to the microorganism component data to the soil according to the degradation rate and the accumulation level.

According to the embodiment of the invention, the soil data is classified by utilizing the data classification module in the support vector machine, so that a large amount of disordered data can be classified into a small amount of similar aggregates by obtaining the classified soil data, and the data processing efficiency can be improved. The classified soil data comprises microorganism component data and pollution metal data, wherein the microorganism component refers to microorganisms such as bacteria anaerobic bacteria, aerobic bacteria, actinomycetes, nematodes and the like which can repair ecological environment, and the pollution metal refers to iron-based metals such as heavy metals of lead (Pb), cadmium (Cd), chromium (Cr) and the like: metal components such as iron (Fe), manganese (Mn), chromium (Cr) and the like which seriously pollute the soil function; the data classification module refers to a part of a module or a component for classifying data in data processing, and generally comprises algorithms, technologies or methods for classifying the data into different categories or groups according to certain standards or rules, and the data classification module can be applied to various fields and tasks, such as text classification, image classification, audio classification and the like.

Optionally, the data classification module in the support vector machine is used for classifying the soil data, the classified soil data is obtained by adding a data tag to each data in the soil data, and the semantics of the data tag are identified by using a pre-trained tag classification function in the data classification module to classify.

Where the tag classification function refers to a function for assigning text data to a predefined set of tags that accepts the input text and assigns it to appropriate tags by analyzing the content, context, or other characteristics of the text, the tag classification function is typically used in natural language processing and machine learning tasks such as text classification, emotion analysis, spam filtering, etc., common tag classification functions include rule-based matching methods, statistical model-based methods (e.g., naive bayes classifier, support vector machine, etc.), and deep learning-based methods (e.g., convolutional neural networks, cyclic neural networks, etc.).

Further, according to the embodiment of the invention, the soil degradation rate corresponding to the classified soil data is calculated by using the polluted metal data, so that the soil removal effect of the metal can be known, wherein the degradation rate refers to the degradation or removal degree of the metal pollutant from the environment under a certain condition.

As one embodiment of the present invention, the calculating the degradation rate of the soil corresponding to the classified soil data using the contaminated metal data includes: inquiring the historical pollution concentration and the current pollution concentration of the pollution metal data, and calculating the degradation rate of the soil according to the historical pollution concentration and the current pollution concentration by using the following formula:

；

The embodiment of the invention can further understand the capability of microorganisms to degrade heavy metals in soil by utilizing the microbial component data to identify the accumulation level of the soil. Wherein the accumulation level refers to accumulation or accumulation of metallic elements in the organism or in the surrounding environment during the microorganism-mediated process.

Optionally, the method comprises the steps of identifying the accumulation level of the soil by utilizing the microorganism component data, observing metal sediment on the surface or in the cell body of the microorganism by using a scanning electron microscope, detecting the metal content in the microorganism cell by using energy spectrum analysis, and analyzing the sediment.

Further, according to the embodiment of the invention, the soil quality restoration level of the soil by the microorganisms corresponding to the microorganism component data according to the degradation rate and the accumulation level can be known, so that the restoration degree of the microorganisms to the soil with an important component in ecology in a certain period can be known, and further, important analysis data is provided for observing the state of the microorganisms to ecological restoration.

As one embodiment of the present invention, the analyzing the soil restoration level of the soil by the microorganisms corresponding to the microorganism component data according to the degradation rate and the accumulation level includes: and identifying the change degree of the active enzyme of the soil according to the degradation rate, identifying the change degree of the acid-base value of the soil according to the accumulation level, and analyzing the soil quality restoration level of the soil by microorganisms corresponding to the microorganism component data based on the change degree of the active enzyme and the change degree of the acid-base value.

Wherein the active enzyme refers to a protein which can catalyze almost all biochemical reactions in vivo or in vitro, including metabolic processes, signal transduction, cell division and the like, and the pH value refers to the pH value.

Optionally, the change level of the active enzyme is measured by fluorescence quantification pcr, and the change level of the acid-base value of the soil is obtained by inquiring the difference between the historical ph record value and the current ph record value of the soil.

S3, analyzing the water eutrophication degree of the water quality corresponding to the water quality data by utilizing a water quality analysis module in the support vector machine, acquiring the historical water eutrophication degree of the water quality, and analyzing the water quality change level of the water quality based on the water eutrophication degree and the historical water eutrophication degree.

According to the embodiment of the invention, the water eutrophication degree of the water corresponding to the water quality data can be analyzed by combining the water quality data by utilizing the water quality analysis module in the support vector machine, wherein the water eutrophication degree refers to water pollution caused by overnutrition in the water.

The water quality analysis module refers to a network layer constructed by utilizing water quality data.

As an embodiment of the present invention, the analyzing the water eutrophication degree of the water corresponding to the water quality data by using the water quality analysis module in the support vector machine includes: generating sample data of the water quality data by utilizing the water quality analysis module, and calculating a water eutrophication rating of water quality corresponding to the water quality data by utilizing the sample data in combination with the following formula:

；

Wherein, the sample data refers to selecting partial data from a large amount of data to represent the overall characteristics.

Optionally, the sample data of the water quality data generated by the water quality analysis module is obtained by uniformly extracting a data set meeting a preset group number (such as 100 groups, 150 groups, etc.) from the water quality data by using a sampling layer in the water quality analysis module, and then performing text conversion on the data set.

Furthermore, the embodiment of the invention can solve the improvement level of the microorganism and the water planting on the water quality in the time period of the historical water eutrophication and the current water eutrophication by analyzing the water quality change level of the water quality based on the water eutrophication degree and the historical water eutrophication degree.

Optionally, the analyzing the water quality change level of the water quality based on the water body eutrophication degree and the historical water body eutrophication degree is performed by constructing a visual chart of the water body eutrophication degree and the historical water body eutrophication degree, and analyzing the water quality change level of the water quality by using the visual chart.

S4, identifying water planting components and harmful substances in the water quality data, inquiring the growth level of the harmful substances, calculating the inhibition level of the water planting components on the harmful substances, and analyzing the improvement level of the water planting components according to the inhibition level and the growth level.

According to the embodiment of the invention, the growth capacity of the harmful substances in the current environment can be known by identifying the water planting components and the harmful substances in the water quality data, so that reliable reference data is provided for analyzing the restoration capacity of the water planting, wherein the water planting components refer to the eutrophication degree of the water body, such as floating leaf plants and submerged plants.

Further, according to the method and the device, the interference caused by the growth of the harmful substances in the process of repairing the harmful substances by the water planting components can be identified through inquiring the growth level of the harmful substances.

As an embodiment of the present invention, said querying the growth level of said harmful substance comprises: creating ecological parameters of the ecological environment corresponding to the harmful substances, inputting the ecological parameters and the harmful parameters corresponding to the harmful substances into a pre-constructed growth analysis model, and analyzing the growth level of the harmful substances by combining the ecological parameters and the harmful parameters by utilizing the growth analysis model.

The ecological parameters refer to corresponding parameters generated according to parameter values of ecological environment data, the harmful parameters refer to corresponding parameters generated according to parameter values of harmful substances, the growth analysis model refers to a model generated for completing a specific task or target, and the structure of the growth analysis model comprises a data input layer, a data preprocessing layer, a data analysis layer and a data output layer.

Optionally, the ecological parameters are generated through binary codes, and the harmful parameters corresponding to the ecological parameters and the harmful substances are input into the growth analysis model through a preprocessing layer of the growth analysis model.

As an embodiment of the present invention, the calculating the inhibition level of the water planting component on the harmful substances includes: identifying effective water planting in the water planting components, and calculating the contribution rate of the effective water planting to the inhibition of the harmful substances by using the following formula:

；

wherein,representing tributeDonation rate->Indicating the number of active water plants, +.>Indicates the quantity of the effective water plants which can inhibit harmful substances>Represents the i-th effective water planting, +.>Indicate->Weight value of effective water planting, < ->Indicating the level inhibition factor of effective water planting on harmful substances, < >>Representing the actual inhibition coefficient of the effective water planting against harmful substances, < >>Represents the j-th hazardous substance;

Wherein, the effective water planting is water planting with improving effect on water eutrophication; the decomposition rate refers to the conversion degree of the water planting to the harmful substances.

Optionally, the effective water planting is inquired about water planting through a big data system to improve water eutrophication data acquisition; the process of calculating the decomposition rate of the water planting component to the harmful substances by using the contribution rate comprises the following steps: and obtaining the product of the contribution rate and the water planting component content.

According to the embodiment of the invention, the improvement level of the water planting components is analyzed according to the inhibition level and the growth level, so that the ratio of water quality in the water quality improvement can be known, and the level of microorganisms in the water quality improvement can be obtained.

Optionally, the analyzing the improvement level of the planting component according to the inhibition level and the increase level obtains an inhibition value and an improvement value by digitizing the increase level and the improvement level, and determines the improvement level of the planting component by using the difference between the inhibition value and the improvement value.

S5, analyzing the water quality restoration level of the microorganism to the water quality according to the water quality change level and the improvement level, analyzing the restoration state of the microorganism according to the soil quality restoration level and the water quality restoration level, and taking the restoration state as a restoration state monitoring result of the microorganism.

According to the embodiment of the invention, the water quality restoration level of the microorganism to the water quality is analyzed according to the water quality change level and the improvement level, so that the restoration degree of the microorganism to water which is an important component in ecology in a certain period can be known, and further, important analysis data is provided for the state observation of the microorganism to ecological restoration.

As one embodiment of the present invention, the analyzing the water quality restoration level of the water quality by the microorganism according to the water quality variation level and the improvement level includes: constructing a water quality improvement curve corresponding to the water quality change level and the water quality improvement level, utilizing the water quality change curve and the water quality improvement curve to perform difference to obtain a difference curve, calculating the curve slope of the difference curve, and analyzing the water quality restoration level of the microorganism to the water quality according to the curve slope. Wherein the curve refers to a state of change of something within a prescribed time.

Optionally, the curve is created by an excel chart tool, the slope of the curve is calculated by a slope formula, the analysis of the water quality restoration level of the water quality by the microorganism according to the slope of the curve is performed by comparing the slope of the curve with a preset slope of the curve, wherein the average level is represented by a preset slope of 0.6, the water quality restoration level is common when the slope of the curve is equal to 0.6, the water quality restoration level is good when the slope of the curve is between 0.6 and 0.8, the water quality restoration level is excellent when the slope of the curve is between 0.8 and 1.0, and the water quality restoration level is poor when the slope is smaller than 0.6.

Furthermore, according to the embodiment of the invention, the restoration state of the microorganism is analyzed according to the soil restoration level and the water restoration level, so that the restoration level of the microorganism in the monitored area to ecology can be analyzed, and the time required for the ecological environment of the monitored area to reach the ideal level can be further analyzed.

As an embodiment of the present invention, the analyzing the restoration state of the microorganism according to the soil restoration level and the water restoration level includes: calculating the monitoring time of the repair area corresponding to the microorganism, inquiring the initial monitoring state of the repair area, and analyzing the repair state of the microorganism according to the monitoring time, the initial monitoring state, the soil repair level and the water repair level. The monitoring time refers to the time length of monitoring the repair area, such as 120 days, 150 days, etc., and the initial monitoring state refers to the initial ecological data level of the repair area, such as soil pollution level, eutrophication level of water body, etc.

Optionally, the monitoring time is obtained by calculating a difference between an initial monitoring time and a current monitoring time, the initial monitoring state is obtained by accessing a database of a repair area corresponding to the microorganism,

Further, in yet another alternative embodiment of the present invention, the analyzing the repair status of the microorganism according to the monitoring time, the initial monitoring status, the soil repair level, and the water repair level includes: performing vector conversion on the initial monitoring state to obtain an initial monitoring vector, performing vector conversion on the soil quality restoration level and the water quality restoration level to obtain a soil quality restoration vector and a water quality restoration vector, and calculating a current monitoring vector corresponding to the initial monitoring vector according to the monitoring time, the monitoring vector, the soil quality restoration vector and the water quality restoration vector by using the following steps:

；

The vector conversion means that data information is digitized to obtain vector data so as to perform mathematical calculation.

Optionally, the vector conversion is realized through a vector conversion script generated by java language.

According to the scheme, the basic information of the area environment can be known by extracting the ecological data of the microorganism restoration area, and the soil data is classified by utilizing the data classification module in the support vector machine, so that a large amount of disordered data can be divided into a small amount of similar aggregates by classifying the soil data, and the data processing efficiency can be improved; secondly, according to the embodiment of the invention, the pollution metal data are utilized to calculate the degradation rate of soil corresponding to the classified soil data, so that the metal pollution removal effect can be known; further, the embodiment of the invention can further understand the capability of microorganisms to degrade heavy metals in soil by utilizing the accumulation level of the soil through the microbial component data, and can understand the current polluted degree of the water body through analyzing the water body eutrophication degree of the water quality corresponding to the water quality data by utilizing the water quality analysis module in the support vector machine to combine the water quality data, wherein the water body eutrophication degree refers to the water body pollution caused by overnutrition in the water body; and identifying the water planting components and harmful substances in the water quality data to know the growth capacity of the harmful substances in the current environment, so as to provide reliable reference data for analyzing the restoration capacity of the water planting, and analyzing the restoration level of the microorganism to the water quality according to the water quality change level and the improvement level to know the restoration degree of the microorganism to water which is an important component in ecology in a certain period, so as to provide important analysis data for observing the state of the microorganism to ecological restoration. Therefore, the method for monitoring the microbial repair state based on the support vector machine provided by the embodiment of the invention can accurately monitor the repair state of the microorganism.

FIG. 2 is a functional block diagram of a system for monitoring the status of microbial remediation based on a support vector machine according to the present invention.

The microbial remediation state monitoring system 200 based on the support vector machine can be installed in electronic equipment. According to the implemented functions, the microbial remediation state monitoring system based on the support vector machine may include an ecological data identification module 201, a soil remediation analysis module 202, a water quality change analysis module 203, a water planting improvement analysis module 204 and a remediation state monitoring module 205.

The module of the invention, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.

In the embodiment of the present invention, the functions of each module/unit are as follows:

the ecological data identification module 201 is configured to extract ecological data of a microorganism repair area, and input the ecological data into a pre-constructed support vector machine, so as to identify soil data and water quality data in the ecological data by using the support vector machine;

the soil quality restoration analysis module 202 is configured to classify the soil data by using a data classification module in the support vector machine to obtain classified soil data, where the classified soil data includes microorganism component data and contaminated metal data, calculate a degradation rate of soil corresponding to the classified soil data by using the contaminated metal data, identify an accumulation level of the soil by using the microorganism component data, and analyze a soil quality restoration level of the soil by microorganisms corresponding to the microorganism component data according to the degradation rate and the accumulation level;

The water quality change analysis module 203 is configured to analyze a water body eutrophication degree of water quality corresponding to the water quality data by using a water quality analysis module in the support vector machine, obtain a historical water body eutrophication degree of the water quality, and analyze a water quality change level of the water quality based on the water body eutrophication degree and the historical water body eutrophication degree;

the water planting improvement analysis module 204 is configured to identify water planting components and harmful substances in the water quality data, query an increase level of the harmful substances, calculate an inhibition level of the water planting components on the harmful substances, and analyze an improvement level of the water planting components according to the inhibition level and the increase level;

the repair status monitoring module 205 is configured to analyze a wastewater content of the production wastewater, perform a second adjustment on the first adjustment parameter based on the wastewater content to obtain a second adjustment parameter, and complete wastewater recovery of the production wastewater by using the second adjustment parameter to obtain a wastewater recovery result.

In detail, the modules in the support vector machine-based microorganism repairing state monitoring system 200 in the embodiment of the present invention use the same technical means as the support vector machine-based microorganism repairing state monitoring method described in fig. 1, and can produce the same technical effects, which are not described herein.

Fig. 3 is a schematic structural diagram of an electronic device for implementing the method for monitoring the microbial remediation state based on the support vector machine.

The electronic device may include a processor 30, a memory 31, a communication bus 32, and a communication interface 33, and may also include a computer program, such as a fired lithium slag forging program, stored in the memory 31 and executable on the processor 30.

The processor 30 may be formed by an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be formed by a plurality of integrated circuits packaged with the same function or different functions, including one or more central processing units (Central Processing Unit, CPU), a microprocessor, a digital processing chip, a graphics processor, a combination of various control chips, and so on. The processor 30 is a Control Unit (Control Unit) of the electronic device, connects various components of the entire electronic device using various interfaces and lines, and executes various functions of the electronic device and processes data by running or executing programs or modules (e.g., executing a firing lithium slag forging program, etc.) stored in the memory 31, and calling data stored in the memory 31.

The memory 31 includes at least one type of readable storage medium including flash memory, a removable hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 31 may in some embodiments be an internal storage unit of the electronic device, such as a mobile hard disk of the electronic device. The memory 31 may also be an external storage device of the electronic device in other embodiments, for example, a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the electronic device. Further, the memory 31 may also include both an internal storage unit and an external storage device of the electronic device. The memory 31 may be used not only for storing application software installed in an electronic device and various data such as codes of a firing lithium slag forging program, etc., but also for temporarily storing data that has been output or is to be output.

The communication bus 32 may be a peripheral component interconnect standard (Peripheral Component Interconnect, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. The bus is arranged to enable a connection communication between the memory 31 and at least one processor 30 or the like.

The communication interface 33 is used for communication between the electronic device and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), typically used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a Display (Display), an input unit such as a Keyboard (Keyboard), or alternatively a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the electronic device and for displaying a visual user interface.

Fig. 3 shows only an electronic device with components, and it will be understood by those skilled in the art that the structure shown in fig. 3 is not limiting of the electronic device and may include fewer or more components than shown, or may combine certain components, or a different arrangement of components.

For example, although not shown, the electronic device may further include a power source (such as a battery) for supplying power to the respective components, and the power source may be logically connected to the at least one processor 30 through a power management system, so as to perform functions of charge management, discharge management, and power consumption management through the power management system. The power supply may also include one or more of any of a direct current or alternating current power supply, a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator, and the like. The electronic device may further include various sensors, bluetooth modules, wi-Fi modules, etc., which are not described herein.

It should be understood that the embodiments described are for illustrative purposes only and are not limited in scope by this configuration.

The roasted lithium slag forging program stored in the memory 31 of the electronic device is a combination of a plurality of computer programs, which when run in the processor 30, can implement the following method:

In particular, the specific implementation method of the processor 30 on the computer program may refer to the description of the relevant steps in the corresponding embodiment of fig. 1, which is not repeated herein.

Further, the electronic device integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a non-volatile computer readable storage medium. The computer readable storage medium may be volatile or nonvolatile. For example, the computer readable medium may include: any entity or system capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM).

The present invention also provides a computer readable storage medium storing a computer program which, when executed by a processor of an electronic device, can implement the method of:

In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus, system and method may be implemented in other manners. For example, the system embodiments described above are merely illustrative, e.g., the division of the modules is merely a logical function division, and other manners of division may be implemented in practice.

The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.

It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.

The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.

It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

The foregoing is only a specific embodiment of the invention to enable those skilled in the art to understand or practice the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. The method for monitoring the microbial repair state based on the support vector machine is characterized by comprising the following steps of:

analyzing the water quality restoration level of the microorganism to the water quality according to the water quality change level and the improvement level, analyzing the restoration state of the microorganism according to the soil quality restoration level and the water quality restoration level, and taking the restoration state as a restoration state monitoring result of the microorganism;

the water eutrophication degree of the water quality corresponding to the water quality data is analyzed by utilizing the water quality analysis module in the support vector machine, and the method comprises the following steps:

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determining the water eutrophication degree of the water quality corresponding to the water quality data based on the water eutrophication rating;

said calculating the level of inhibition of said harmful substances by said water planting composition comprising:

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2. The method of claim 1, wherein calculating the degradation rate of the soil corresponding to the classified soil data using the contaminated metal data comprises:

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3. The method of claim 1, wherein analyzing the soil restoration level of the soil by the microorganisms corresponding to the microorganism component data based on the degradation rate and the accumulation level comprises:

4. The method of claim 1, wherein said querying the growth level of the hazardous substance comprises:

5. The method of claim 1, wherein said analyzing a water quality restoration level of said water quality by said microorganism based on said water quality variation level and said improvement level comprises:

6. The method of claim 1, wherein said analyzing the repair status of said microorganism based on said soil repair level and said water repair level comprises:

7. The method of claim 6, wherein said analyzing the repair status of the microorganism based on the monitoring time, the initial monitoring status, the soil repair level, and the water repair level comprises:

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8. A support vector machine-based microbial repair status monitoring system for implementing a support vector machine-based microbial repair status monitoring method according to any one of claims 1-7, the system comprising:

The water planting improvement analysis module is used for identifying water planting components and harmful substances in the water quality data, inquiring the growth level of the harmful substances, calculating the inhibition level of the water planting components on the harmful substances, and analyzing the improvement level of the water planting components according to the inhibition level and the growth level.